 |
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Introduction What follows is meant as a summary or brief overview only of this topic area. It is essential that a combination of class exercises and/or texts are used with the notes to provide a fuller understanding of the issues covered. Easily the best way of learning research methods is a combination of reading followed by practise. Read a section, e.g. on levels of data and then practise what you’ve just learned by answering questions on the topic. Questions on the paper will require short response answers.
An overviewThe board requires that you have knowledge of the following areas and some texts cover them in this order.
Ethical issues Deception Consent Right to withdraw Protection from physical and psychological harm Dealing with ethical issues e.g. debrief, committees and guidelines
Research Methods
Research Design and implementation Aims and Hypotheses Research design Independent, dependent and extraneous variables Sampling Pilot studies Reliability and validity Demand characteristics and investigator effects
Data analysis Analysis of quantitative data Measures of central tendency and of dispersion Correlation coefficients Presentation and interpretation of quantitative data Analysis and interpretation of qualitative data Presentation of qualitative data
However, this is not a logical teaching order so although this booklet will cover all the stuff mentioned above it will follow a different sequence and hopefully one more similar to the route taken in class.
Government Health warning The following information does contain sums and other material likely to cause offence to the squeamish. However, I’ll endeavour to keep the aforementioned to an absolute minimum and will, wherever possible avoid the gratuitous use of numbers!
Ethical issues in Psychological research Ethics are the moral codes laid down by professional bodies to ensure that their members or representatives adhere to certain standards of behaviour. All scientific bodies have such codes but those in psychology are particularly important because of the subject matter of the topic. 1. Psychology is unlike most other subject areas in that its subject matter is entirely human or animal. Because of this practically all research involves living things that can be caused physical or psychological harm. 2. Psychological research also needs to consider the wider community. Milgram’s research taught us something unpleasant about the human race in general. Some research, for example studies on IQ, have been used to discriminate against different races or ethnic groups. It could be argued that Bowlby’s research was used to discriminate against women, making them feel guilty for not being at home caring for their children. 3. The knowledge gained from psychological research can be exploited by people or groups to gain an advantage over others. Skinner’s work on behaviour shaping could be abused in this way.
Protecting the individual in psychological research Many of the ideas mentioned in this section will be raised as we cover other topics later in the year and particularly in the last topic on social influence.
We shall then consider ways of determining whether or not studies should take place, and strategies for minimising risks if they do.
Deception Examples of studies involving deception: Asch, Milgram, Cruchfield Deception involves either concealing the real intention of a study from participants or taking steps to mislead them at the outset. All of the examples above used the second ploy, deliberately lying to participants about the genuine reason for a study. Two of them also used stooges or confederates (people pretending to be participants who are really part of the experimental set up). The use of stooges always means deception has been used. However, is deception necessary? The researchers above would all argue that their experiments could not have taken place without it. Imagine if Milgram had said at the start, ‘Mr Wallace is really a stooge, who will scream a bit but will receive no shocks.’ The study would have told us nothing of interest and obedience would doubtless have been close to 100%. To a lesser extent nearly all studies involve an element of deception in that it generally isn’t a good idea to tell your participants what you are looking for in advance. Menges (1973) estimated that as few as 3% of studies involve no deception at all. When using the BEM sex role inventory to test gender, telling male participants in advance that you are trying to find how masculine or feminine they are will almost certainly influence the way they respond to the questionnaire! Baumrind on the other hand argues that deception is always wrong since it prevents informed consent (see below), researchers have an obligation to protect their participants (see below) and psychologists should be seen as professional and therefore trustworthy.
Debriefing It is really a matter of common courtesy to debrief your participants at the end of any procedure and inform them of the point of the research. Debriefing is crucial if any form of deception has been employed. A proper debrief should: 1. Inform participants of the purpose of the research 2. Ensure that there are no negative or unforeseen consequences of the procedure 3. Ensure that the participant leaves in ‘a frame of mind that is at least as sound as when they entered.’ (Aronson 1988). 4. Give the participant the right to withdraw their data and to see the finished write-up of the report if they so wish. As well as having the best interests of the participant in mind, debriefs can also be a useful source of additional information in an experiment. Participants may tell you things that you would otherwise not be aware of.
Therapeutic debriefing In extreme cases such as Zimbardo’s study, participants may receive questionnaires, be asked to complete diaries and have follow up meetings with the experimental team. In the case of Milgram some participants also received follow up psychiatric visits!
Consent and Informed consent Consent Simply refers to participants willingly and voluntarily taking part in your experiment. Milgram and Asch for example did obtain consent. In the case of Milgram he placed his infamous advert in the local paper and people turned up. During WWII the Nazis carried out many procedures on prisoners without their consent. Following the war it was decided that consent should be enshrined as a basic human right. Informed consent This refers to participants giving their consent in full knowledge of the aims of the study, the expectations of them and their right to withdraw and to confidentiality. This clearly was not the case with Asch or Milgram, but arguably was with the Zimbardo procedure. This raises the issue of whether fully informed consent is ever possible. If researchers know the likely outcomes of a study then what is the point in carrying it out in the first place? Informed consent and deception are closely related in that there cannot be informed consent in any situation where deception is used.
Special cases
Various ways of overcoming the issue of consent will be discussed later. These include presumptive consent and prior general consent.
Protection from physical and psychological harm Physical harm The BPS guidelines suggest that participants should be exposed to no more risk than they would be in everyday life. For example people driving cars are exposed to a certain level of risk. If psychologists wish to study some aspect of driving related behaviour then the procedure they use should not put their participants at greater risk than this. There are occasions when researchers have caused their participants physical harm although these tend to be rare. Milgram appears to have delighted in the response of some of his participants who would ‘bite their lips and dig their fingernails into their flesh. Full blown, uncontrollable seizures were experienced by three subjects.’ (Wrightman and Deux 1979). Psychological harm This is more difficult to gauge but may involve embarrassment, loss of self esteem, stress and anxiety. Asch, Zimbardo and Milgram procedures would all have involved loss of self esteem, embarrassment and some stress, and in the case of Milgram and Zimbardo, extreme anxiety. Confidentiality is one way of protecting participants from psychological harm. If you do something shameful or embarrassing then others not knowing will help reduce the impact.
Confidentiality The data protection act requires that the identity of all participants remains confidential. As well as safeguarding privacy there is an obvious practical benefit from this approach. Participants are unlikely to volunteer for procedures if they believe that their identity and behaviour will be divulged. There were clear breaches of confidentiality in the Milgram and Zimbardo studies as in both cases participants were secretly filmed.
Guidelines require that participants are not identified unless they give their permission and various methods may be used to disguise their identity. For example in case studies patients may be identified only by their initials such as KF or HM.
The right to withdraw and to withdraw data This should be available and made clear to participants before the research starts. Both Milgram and Zimbardo claim that withdrawal was possible in their studies although when questioned afterwards it is clear that not all participants realised this. Advance payment was an issue in the Milgram study. This may put additional pressure on participants who may feel obliged to earn the money that they have received. The debrief should make it clear that participants have the right to withdraw their data on being told the nature of the study. If serious deception has taken place then participants have the right to witness their data being destroyed!
Dealing with the ethical issues This is a favourite question in which you are expected to describe and/or evaluate measures taken by psychologists to minimise the adverse effects of research. Obvious points to mention would be seeking consent, avoiding deception, providing the right to withdraw, debriefs and confidentiality. For fuller marks some or all of the following could also be discussed:
Ethical guidelines and codes of conduct Following the immoral experiments of the Nazis in WWII, each country set up its own set of guidelines for performing scientific research. In Britain the British Psychological Society (BPS) and in the USA the American Psychological Association (APA), produce codes of conduct for both experimentation and for clinical practice. For human participants the codes cover topics already mentioned such as deception, consent, withdrawal of data, confidentiality etc. Additionally all institutes that perform psychological research have ethical committees that consider whether or not particular pieces of research should be carried out. This body should have non psychologists that can express more objective views on research. Cost-benefit analyses Committees may carry out cost-benefit analyses in which the likely benefits of a particular piece of research is weighed up against the costs to human or animal participants. Put simply does the knowledge we gain about human behaviour and the advantages this might have for the wider population warrant the suffering or embarrassment of a few individuals? Such analyses are notoriously difficult to carry out objectively, particularly in advance of a piece of research. Psychologists still argue about the costs and the benefits of the Milgram procedure, and that’s with the benefit of forty years of hindsight! Additionally the costs to the larger social group may also be considered, for example and an ethnic or racial group or women etc. Obtaining consent and avoiding deception Presumptive consent (of ‘reasonable people’) This asks people for their views on a particular procedure. If generally they find it acceptable then that procedure is used… but NOT on those asked. Prior general consent A pool of possible participants would be asked for their views on research. For example they may be asked about their views on the use of deception or embarrassment during research. Only those participants who consider these ploys acceptable would then be selected for later research involving fibs etc. Role playing People are asked to act out the role of participants in problematical studies involving deception or psychological harm etc. Clearly these are less than satisfactory since people can only guess at how they would respond in such situations. When asked, fewer than 1% of people believe that they would obey in Milgram’s study!
Research Methods
The Experiment
Definition
In an experiment a variable is manipulated to see what effect it
will have on another.
For example
if we wanted to know whether caffeine affected reaction times:
We could
take two groups, give one group coffee (experimental group) and compare
them to another group without coffee (control group).
We would then set them a task designed to measure their reaction
times.
In
experiments there are 2 variables:
Not rocket
science, BUT the problem is always remembering which is which.
The way I do it is simply to think of the dependent
variable as the one that depends on what we do!
In this case
reaction time (dependent variable) depends on whether or not the
participant has had a cup of coffee.
Crucially an
experiment allows us to establish a causal link between the IV and the
DV. Following an experimental procedure we should be certain that the
alteration we have made in the IV has caused the change in the DV. Other
variables
The I.V. and
D.V., as we psychologists refer to them, are not the only variables to
worry about.
In the
coffee experiment suppose we find that the coffee group have faster
reaction times, can we be certain the coffee has caused this.
Other possible reasons:
Confounding variables These are variables that get in the way of our results or make our results difficult to interpret. Think of Brady’s executive monkeys. Brady assumed that being in control had caused the stress that lead to the ulcers. Control being the IV and ulcers being the DV. In fact it was more likely to be the activity levels of the monkeys that caused the results. This is an example of a confounding variable. Common confounding variables include:
Obviously in an experiment we take steps to minimise these, for example we could ensure that the procedure is carried out at the same time of day, in the same room, with similar temperature settings etc.
Laboratory experiments Lab experiments don’t have to be carried out in a laboratory. However, any experiment that is carried out in a special, tightly controlled environment is classed as laboratory. Importantly it is obvious to those taking part that that they are in an experimental procedure. Laboratory experiments are therefore artificial and tightly controlled, leading to the following advantages and disadvantages:
Laboratory experiments we have seen this term: Most studies on memory would have been lab experiments: Brown-Peterson technique, Baddeley’s study of encoding, Loftus’ research into leading questions, Sperling’s study of sensory memory etc… Not all experiments however are carried out in artificial settings and not all allow full control of the IV. Other types of experiment are covered next:
Field experiments Not, as the name implies, experiments conducted in fields, although they could be! More likely settings would include the work place, school, the street etc. Basically the same rules apply: an independent variable is manipulated to see how it affects a dependent variable. Confounding variables can still get in the way, and cause and effect can still be determined. However, the setting is more natural.
In practice it can be difficult to distinguish a laboratory experiment from a field experiment. Consider the Brewer and Treyen’s office schema study. This is clearly an experiment and in an artificial setting, but the participants were not aware at the time of the procedure, that they were taking part in a study so there behaviour was quite natural. Similarly with Loftus’ study on weapons focus. Participants listened to an argument whilst waiting to start an experiment. Again the setting was artificial and there was full control over the IV (blood soaked knife or pen). However, again the participants were unaware of the procedure so again their response would have been natural. Are these laboratory experiments or field experiments? No right answers really. However, the crucial thing is that you can justify your answer and explain the positive and negative points.
Natural experiments Not, as the name implies, experiments carried out in the buff, although they could be if you were comparing the memory of those who naturally prefer to go au naturelle with those who prefer to wear clothes. These are similar to and often confused with quasi-experiments, but there is one crucial difference. Natural experiments take advantage of a naturally occurring event. The effect of the eruption of Mount St Helens on stress related illnesses is the one all the texts prefer to mention. In this case the IV was the eruption, a naturally occurring event. A better example and one that we’ve studied is Hodges & Tizard’s study of institutional care which examined the effect of different types and duration of care on the children’s subsequent behaviour and development. IV is the type and duration of care (in this case not controlled by the researchers, it happened anyway). DV is the effect this has on subsequent development (and which can be measured using various tests).
Quasi-experiments Not, as the name implies, experiments were you run around in the dark pretending to shoot each other with lasers! But they could be if you were looking for age or sex differences. In a real experiment you can manipulate the IV and you can decide who goes in which group. In your study on coffee you decide which participants go in which group. However supposing you wanted to see if 40-somethings had faster reactions than teenagers: you never know it could happen! In one group your participants will have to be teenagers and the other group will have to comprise 40-somethings. You are unable to randomly allocate your participants to the different groups. Similarly with sex differences; by definition the boys are going to be in one group and the girls in the other!
Experimental research design Here we decide how we are going to sort or group our participants. Do we use the same people in all conditions or groups, or do we choose different people for different conditions or groups? In some cases, as we’ll see the decision is made for us. In others the solution isn’t so obvious and there may be pros and cons for each.
Repeated Measures Design Here we use the same participants in each group or condition. For example, returning to the earlier experiment on coffee and reaction times. In a repeated measures design we could give our group of participants the test on day one with no coffee and record their reaction times. The next day we could repeat the procedure, with the same group of people, but this time give them coffee before the experiment began.
Advantages The two groups have the same age, sex, personality, ideas, past experiences, IQ, reaction times (crucially for this one) etc. They are perfectly matched. They are the same people!
Disadvantage Order effects: Assuming, as we expect the group do better on the second day, can we be sure that this increase in performance is due to the coffee? It could be that they’ve had the chance to practice the task the day before! It’s not surprising they’re better the second time around. This is called order or practice effect. Boredom: Of course, on some tasks it could work the other way, and a task done the second time shows a deterioration because they’re fed up with doing it. Extra materials: For example if you use the same participants for two memory experiments you will need two lists of words etc. for them to recall. This introduces other variables. Perhaps the second list is easier than the first.
Independent Measures design You guessed it. If we used the same people in each group last time, this time we use different people in each group. Clearly this overcomes practice and boredom effects ‘cos they only do it the once! Each participant is randomly allocated to one group or the other, so in our coffee experiment: One group, comprising one set of participants do the test with coffee The other group, comprising a different set of participants do the test without coffee. Sorted, no problems with practice or repeat effects or with boredom or tiredness effects.
However Can we be certain that the likely faster reactions of the first group are down to the coffee? It could be that the participants that we’ve randomly assigned to that condition have naturally faster reactions. They may be younger, or some of them may engage in activities that require fast reactions. In other experiments, sex, personality, age, IQ etc. could all be an issue because the participants are going to differ on all of these. There are some occasions when independent measures design has to be used: Sex differences Age differences By definition the two conditions are different. You couldn’t have someone in the male condition and the female condition, or in the under 30 condition and the over 30 condition! Advantages 1. No order or practice effects 2. Can use the same stimulus material (such as word lists in memory) for each group Disadvantages 1. Participants are not matched in terms of IQ, personality, age etc. 2. You will need twice as many participants. Clearly these are the same as the advantages and disadvantages of repeated measures but in reverse.
Matched Pairs Design This is the ideal compromise. In the reactions experiment you would have different people in each condition, i.e. some would have the coffee and others not. However, the two sets would be matched in terms of IQ or whatever characteristics are relevant, in this case reaction times, age etc. Advantages 1. No order effects since each participant only does the task once 2. You can use the same material twice 3. Groups are similar in terms of individual characteristics
Disadvantages 1. Very time consuming and difficult to match all of your participants in this way 2. It is impossible to match people for all characteristics even if you were to use MZ twins between the two groups!
Observations
Naturalistic Observation This is an easy one to explain. People or animals are observed in their natural environment, without any sort of intervention or manipulation of variables and without their knowledge. Examples include:
Ethologists specialise in studying animals in their natural environment.
The researcher observes behaviour in its natural environment as many of the ethologists studying animal behaviour record their information. Ainsworth’s study of attachments in Ugandan women would be a human example of naturalistic observation.
Controlled As the name suggests the researcher in some way manipulates the behaviour of the observers or the observed. Ainsworth’s strange situation is the best example seen to date with researchers organising the behaviour of the mother and stranger to see how the child reacts. Other examples include the Bobo dolls and Piliavin’s work on bystander apathy on the New York subway. These allow for greater control of confounding variables meaning it is easier to establish cause and effect relationships. However, they are lower in ecological validity since the trigger for the behaviour is usually not a natural event. Often, but not always, participants may also know they are being observed creating demand characteristics. Disclosed Participants know they are being observed. This reduces ethical issues of consent and privacy but reduces validity due to increased demand characteristics. Undisclosed Participants are unaware of the observation. This raises ethical issues (privacy and consent) but increases validity by reducing demand characteristics. Sometimes one way mirrors might be used to discretely observe people, for example shopping behaviour in a supermarket.
Participant Here the researchers get involved with the group of participants they are observing. Festinger (1956) joined a cult to observe how they would react when their predicted end of the World deadline came and went. The cult leader was able to reassure his flock that their prayers had saved the planet! This is an example of undisclosed participant observation. On occasions researchers may join in but make others aware of their role as psychologists. On occasions researchers have been able to infiltrate groups and remain members for a period of time allowing for detailed, longitudinal information to be gathered, for example about the behaviour and motivations of street gangs and religious cults. It is difficult to see how such groups could be studied in any other way. Clearly there are ethical issues with this type of deceitful observation and the researcher themselves may unwittingly interfere with the group dynamics and the behaviour of the group. Non-participant The more likely scenario in which participants are observed from a distance rather than the researchers infiltrating the group.
Ethics of observations Observations raise a number of unique ethical issues. These vary depending on the nature of the observation taking place but here are a few: Consent: participants are often unaware of being observed so have no opportunity to consent to taking part in your research. Debrief: often there is no opportunity for a debrief. For example in Piliavin’s observation of bystander apathy on the New York subway, participants were observed without their knowledge and would have left the train before researchers had chance to debrief. Deception: participants being unaware of observation is deception in itself. Additionally, researchers may cause additional deception by using stooges. Again Piliavin used members of the research team to pretend to be blind or drunk.
Correlational analysis In the past year we’ve seen lots of examples of this. For example whenever I’ve criticised a study because it doesn’t show cause and effect it’s probably been a correlational study. An example: For example we could look for a correlation between IQ and performance at GCSE or A-level. Common sense would perhaps tell us that students that have higher IQs are more likely to perform well at GCSE. In year 13 we look at the controversial area of IQ and find that there is a high correlation between the IQs of MZ twins. If one twin has a high IQ it is likely the other does too. This is taken as evidence for the nature or genetic determination of IQ. However, as we will see there are a host of other reasons why this might be the case. Types of correlation Positive: the most common; as one variable increases so does the other, e.g. IQ and GCSE score in the example above.
Positive Negative
Negative: as one variable increases the other decreases, e.g. it might be fair to assume that the higher your stress levels the lower your life expectancy. Again we are unable to show cause and effect. As mentioned frequently in ‘Stress,’ illnesses could be due to secondary habits such as smoking, poor diet etc.
Case studies These involve study of an individual, small group, institution or an event. A case study can involve a whole host of techniques including observations, questionnaires, surveys, interviews, testing and even on occasion experiments. They are frequently longitudinal in nature and may also involve asking others, such as friends and associates. Examples: Clive Wearing, HM, KF, S, Genie, Czech twins, Anna O, Little Albert, Little Hans, Phineas Gage
However They it is notoriously difficult to generalise from a case study and create a general theory. Case studies by their very nature are one-offs or unusual and often involve people who are not themselves representative of the general population. The case of Genie and the Czech twins shows this nicely. Both suffered severe deprivation over a prolonged period but their outcomes are very different; the Czech twins seeming to make a full recovery, whereas, as far as we know, Genie never recovered from her early problems. Often case studies require an element of retrospective data collection, with parents, friends etc being asked to think back to the participants earlier years. Retrospective data collection is not reliable. Objectivity by the researchers can be difficult, with psychologists getting too close to patients as with the case of David Rigler and Jean Butler and their research/fostering of Genie. Confidentiality can be an issue though some of this can be overcome by the use of pseudonyms or initials.
Interviews There are a number of species of interview each with their own advantages and disadvantages. I’ll consider the main ones only: Informal interviews The interviewer has an aim in mind at the outset but is willing to be flexible about getting answers. The interviewer tries not to direct the interviewee but instead listens and lets the interview take its natural course.
Clinical interview These were made popular by Freud and in particular Piaget and are a type of informal interview. Piaget for example would read ‘moral stories’ to a child and start off by asking the same questions to all the children, for example ‘who is the naughtier boy in the stories.’ However, follow up questions would be informal and vary from child to child.
Structured or formal interviews These follow a set pattern with the interviewer having prepared a set of questions in advance that are asked in a particular order. Note: sometimes the questions may be open and allow the interviewee to respond how they like, for example ‘how did you feel when Freddie ate your pet hamster?’ Or they can be closed and allow only a ‘yes’ or ‘no’ response. For example ‘were you upset when Freddie ate your pet hamster?’
Limitation of interviews in general: Social desirability bias We all like to create a favourable impression. When faced with an interviewer we are less likely to be honest than when filling out an anonymous questionnaire. For example people being questioned about their love life are likely to exaggerate in face to face interviews. Lie scales can be introduced to assess how honest answers may be. For example if people were being questioned about their childhood a ‘lie question’ might be; ‘As a child did you always do as you were told first time and without moaning?’ A response of ‘yes’ would be assumed to be a fib and indicate that perhaps the interviewees answers may not be reliable.
Questionnaires We all know what they are and have all filled lots of them in. Basically a questionnaire is a list of written questions that is able to gather lots of relevant information relatively quickly and cheaply. The biggest problem is wording of the questions. Again there is the issue of ‘open’ or ‘closed’, but more importantly, as we saw in EWT, the issue of leading questions. These are a favourite of politicians or of newspapers that want to find support or criticism of a particular issue. For example imagine you wanted to find out if people wanted more money spent on the NHS, a relatively neutral question might be ‘Should more money be spent on the NHS?’ The Mirror (presumably wanting a ‘yes’ response might get their pollsters to ask: ‘Should extra money be provided to the NHS to take care of Britain’s sick and elderly?’ Whereas the Telegraph (being very stereotypical here) may get their pollsters to ask: ‘Would you be happy to pay more taxes to fund bureaucracy in the NHS?’
Rather extreme examples admittedly, real surveys carried out by experienced pollsters would be far more subtle, but you get the idea! It is always a good idea to test your questionnaire in a pilot study first to make sure it doesn’t take hours to complete and that participants understand the questions. Feedback like this may provide ideas for follow up questions to be asked in the real study.
Typical questions on Research Methods Describe two disadvantages of investigations using correlational analysis (2 + 2 marks) Identify the research method used in this study and explain one advantage and one disadvantage of this method. (2 + 2 marks) Give one advantage of using a questionnaire in this study. (2 marks) Following the survey it was decided to carry out an observational study into under-age drinking. Outline procedures for carrying out such an observation. (6 marks)
Content analysis Content analysis studies human behaviour indirectly usually by studying the things we produce, e.g. television programmes, magazines etc. An analysis of what we produce should be able to tells us a lot about the way we structure our society and about our values, prejudices and so on. For example a content analysis of television advertisements of the 1970s would probably paint a far more sexist view of the World than that present today, certainly in the UK at least. Manstead and McCulloch (1981) watched 170 television advertisements in a week and scored them on a whole range of factors such as gender of product user, gender of person in authority, gender of person providing the technical information about the product and so on.
Good points They can produce lots of detailed and easily analysed material about a particular aspect of society. Since the research is observational it is high in validity. Provided the information is well presented and sufficient records are kept and published relating to the material sourced and the content analysed replication and verification of results should be possible. However There is the possibility of bias, with the observations being subjective. To overcome this a number of raters should be used (inter-rater reliability) The choice of material and content to be analysed also introduces a potentially huge source of bias.
Other research methods As already stated, many research studies use a combination of techniques. We saw this with case studies but as Cardwell and Flanagan point out, Schaffer and Emerson’s Glasgow babies study used natural observation, interviews and even occasionally experiments when mothers recorded how the children responded to a series of everyday events. Meta analysis The results of a number of studies (usually buy a variety of researchers) in a related area are combined to see if overall trends are visible. This can increase reliability since contradictory findings may be uncovered. However, different studies may be difficult to compare because of different sampling, design and methods used. Longitudinal studies A favourite with developmental psychologists since they allow children to be revisited to see how they change and grow over time. The big disadvantage is attrition. People move to different areas or become impossible to contact.
Research Design and Implementation Aims and Hypotheses Aims When carrying out a piece of research it is essential that you have an aim in mind. This needs to be reasonably precise, for example ‘I’m gonna study memory’ would not be sufficiently precise. However the aims are broader, or less precise than the hypotheses. A suitable aim for memory might be ‘to see if age affects the duration of STM.’ Miller’s aim was to discover the capacity of STM. Milgram’s aim was to see if normal people would obey when told to kill someone!
Hypotheses These are more precise and should be operationalised, i.e. give some clue as to how the research will be carried out. You must remember that two hypotheses are included: a. Experimental or alternative hypothesis This makes your prediction, for example: ‘As age increases the duration of STM decreases.’
b. Null hypothesis This might at first glance seem redundant, since what you are saying is that you will not find what you’re expecting. A suitable null hypothesis for the experiment above could be: ‘Age will have no effect on the duration of STM.’
The two examples above are simplified to give you the overall idea. When deciding on an experimental hypothesis you need to give some indication of the method to be used. For the above experiment it might be: ‘Duration of STM, as measured by the Brown-Peterson technique, will decrease with age.’ The null hypothesis would normally read: ‘Age will have no affect on duration of STM. Any effect found could be due to chance.’ Why do we have a null hypothesis? A null hypothesis is easier to prove. For example if we were trying to show that all MZ twins had the same voting intentions. Our hypothesis might be: ‘Pairs of MZ twins will always vote in the same direction in the coming General election.’ The null hypothesis might be: ‘Twins status will have no affect on direction of voting. Any similarity found may be due to chance.’ Suppose we test 50 twins and both members of each pair are intending to vote in the same direction. Have we proved that all twins will vote in the same direction? It could be that the next pair we test won’t. In that case all we need to do is find one pair that have different intentions to prove our null hypothesis. When we finally get round to testing the results with a stats test it will be the null hypothesis that we’re testing.
One tailed or two tailed? Having decided on your hypothesis and aims you need to decide on the direction. In the examples above I’ve already done this. When we say that we expect ‘duration of STM to decrease as age increases’ we are making a definite prediction. That prediction has direction. Compare this to the statement that ‘duration of STM will be affected by an increase in age.’ Will duration increase or decrease? The hypothesis doesn’t say. It could go either way. One tailed If the hypothesis has a direction we say it is ‘directional’ or one-tailed. In the first example we are saying that duration of STM will decrease. Two tailed If we are not prepared to commit ourselves and simply say there will be an affect then this is non directional or two tailed. Try the exercises for practice and further illumination. In year 13 coursework you will almost certainly be copying (sorry replicating) someone else’s work, for example Peterson and Petersons. In this case your hypothesis will be based on their research. If you were to replicate Milgram’s (don’t even think about it), you would choose a one tailed hypothesis such as: ‘Participants will follow instructions and fry an innocent person with 450V of electricity when told to do so by a man in a white coat.’
You could predict this with some confidence since all past research suggests that this is the case. Note: this business of one or two tailed does not apply to the null hypothesis. This will always read, “not be affected” or “no correlation” etc.
Selecting your victims (sorry participants) Having decided on your method (experiment, correlation etc.) and your design (repeated or individual) you now need to decide how you will choose the people who will be assigned to your conditions or groups. When asked, everyone replies in unison (not the Trades Union): ‘RANDOMLY. WRONG!!!
Random Sample It is practically impossible to get a truly random sample. In a random sample every member of your target population would have an equal chance of being selected. So for example if you wanted a random sample of primary school children in the Market Harborough area you would need to obtain all of their names, put them in a hat and draw your sample out. In actual fact that would be the easy bit. The difficult task would be finding them and persuading their parents to let you chosen ones take part! The main disadvantages of this method are: 1. Time consuming 2. Inevitably some of those selected will not take part Other, more realistic methods of obtaining a representative sample:
Systematic sample (similar to random, with the same disadvantages) This could be done by visiting the target schools and selecting every 5th child in the register. This would still be time consuming. If your target was people in MH, you could select every 20th street and then visit every 10th house in those streets etc. However, it cannot be claimed that every person in MH has an equal chance of being selected!
Stratified sample Here each variable affecting the outcome of the procedure needs to be considered. For example if you were investigating voting intentions you would want to select on grounds of: gender, occupation, age, education, home ownership etc. So because the male:female ratio is about 50:50 your sample would be 50:50. Because about 65% of the adult population are home owners then 65% of your sample would be too. Etc., etc. Disadvantages Time consuming Not a truly representative sample
Opportunity sample Now we’ve hit rock bottom! This is probably the least effective way since it involves selecting whoever happens to be available and willing to take part! Next year in your search for victims, chances are you’ll go to the sixth form centre and pick out a few friends or non-threatening strangers. Valentine (1982) estimates that 75% of all American and British psychology research is conducted on students, and the majority of these will have been selected in this way! Disadvantages A very poor representative or cross-sectional sample!
Sample Size How many people are going to be part of your opportunity sample? Things to consider: Large samples can be expensive and are definitely time consuming Small samples make it difficult to get a significant result (20 is about the minimum for most statistical tests). Generally, the larger the sample the better since bias is likely to be reduced.
Reliability and Validity Both of these have been mentioned during the year, particularly ‘validity’ as in ‘ecological validity’ or ‘experimental validity.’ However, you now need to fully understand what both of them mean, how they can be increased and most importantly how to remember which is which! Reliability Reliability is akin to consistency If you use a meter rule to measure the length of your classroom today, and you repeat the procedure next week, you will expect to get the same result. The meter rule is consistent in its measurement or we say it is reliable! Reliability in Psychology This can be measured in a number of ways depending upon the circumstances. However, each time we are looking for consistency of measurement: Reliability of observations This year some of the students have observed aggressive acts in men’s and women’s football to see if the men’s game is really more aggressive. (Personally I never realised that real men played football but that’s a different issue). Inter-rater reliability One way of tackling this problem would be for one person to watch a game played by each gender, look for various aggressive acts and score them accordingly. However, you only have one person’s opinion. Better would be to get two or three people to do it independently and compare scores afterwards. To ensure that results were reliable the raters would sit down beforehand and decide on the criteria to use and how to apply these. For example decide exactly what was meant by ‘dirty tackle’ (no jokes please) or an ‘aggressive act.’ This would ensure inter-rater reliability. Or in English it would ensure consistency in measurement between the observers. All singing from the same hymn sheet in politico-speak.
Reliability of tests If you measure someone’s IQ today you would expect to get a similar result if you used the same test to assess the same person in a few weeks time. If the results were the same time (i.e. if the results were consistent (that word again)), you could assume the test was reliable!
Validity Does the test or the experiment measure what it’s s’pose to be measuring? We have mentioned this word ‘validity’ on a number of occasions, usually in relation to ‘ecological validity.’ However, there are a number of different types of validity; here we’ll concentrate on ‘internal’ and ‘external’, sometimes referred to as ‘ecological.’ Internal (or experimental) Validity Are the effects that have been caused actually due to the independent variable? For example if we’ve found that coffee (the I.V.) does increase speed of reaction (the D.V.), can we be certain that this increase is really due to the coffee or could it be due to a confounding variable such as the time of day or just faster reactions of the second group etc. Basically any of the confounding variables mentioned so far such as IQ, gender, age, time of day, lighting conditions etc., can cause false conclusions to be drawn.
External validity (like ecological validity) How much can the results obtained tell us about real life, or put another way; can we generalise our findings to the real world? Coolican (1994) points out 4 major issues:
Methods of checking validity Clearly it is useful for a psychologist to have some idea of whether or not tests are valid. There are a number of ways this can be done: Meta analyses: data can be collected form lots of different studies in different parts of the World and see if results are similar. For example Bouchard & McGue compared findings for IQ tests between MZ twins and found similar levels of correlation between them all. Concurrent validity: if we are measuring IQ we could compare the scores obtained to school tests in maths and English, or we could compare the results of personality tests with assessments by a person’s friends and family. Predictive: a test should be able to predict later performance, behaviour or personality. So again, a high score on an IQ test should be able to predict later success at school etc. In school you sit YELLIS and ALIS tests which are used by teachers as predictors of your future performance.
Relationship between researcher and participant As we’ve already seen this can cause problems, particularly in the experimental method. In the Milgram evaluation I touched on demand characteristics, the idea that simply because the participant was taking part in an experiment that this would affect his behaviour (all Milgram’s participants were ‘he’s). Possible effects: Participant reactivity Put simply, participants will behave differently or unnaturally because they know they are being watched. This doesn’t just apply under experimental conditions but in any walk of life! The classic example which is well worth a read, but not necessary for the exam, is to be found on page 272 and is known as the ‘Hawthorn Effect.’ Demand characteristics The idea that participants will behave the way they believe you want tem to behave. It could be that participants guess what the experiment is about, or at least think they’ve guessed, and this will influence their behaviour accordingly. This was a criticism of the Milgram procedure. In Asch’s study on conformity, some of the participants said afterwards that they conformed because they didn’t want to mess up the experiment! Orne (1962) persuaded participants to do strange, if not very foolish things. This argument is often used in the debate over hypnosis. Orne, for example, persuaded his participants to put their hands into a tank containing a supposedly very venomous snake. His most famous ‘experiment’ was to persuade participants to spend hours adding up random numbers and then getting them to tear up all their hard work! Sometimes, of course, the reverse may be true, and for whatever reason, e.g. having been conned in previous studies, participants may deliberately seek to mess up your experiment by behaving counter to how they think you want them to behave.
Reducing demand characteristics The most common ploy is called the single blind technique in which participants are not told details of the study or in which they are led to believe it’s about something different. This is a ploy I used in my research on hypnosis. (Will bore you with the details sometime soon!). Clearly this raises ethical issues such as deception and informed consent.
Investigator effects A confession. As a sixth former, many years ago, I spent, what seemed at the time, about five years doing titrations in A-level chemistry. Not one of the results I obtained was genuine. We calculated the ‘right answer’ for all of them and then obtained a reading that was close to this. This was cheating, and we know that results in Psychology have also been fiddled, some on a grand scale. Obtaining ‘expected results’ like this can be deliberate. Or it can happen without intent. We often find what we are expecting or hoping to find. Having decided that women are worse drivers we notice bad driving by women whilst ignoring similar driving by men. This happens in research and is called experimenter expectancy. The classic example is Rosenthal and Lawson (1964). They gave rats to students, telling some that their rats were ‘maze bright’ and could navigate a maze very quickly, and telling others that their rats were ‘maze dull’ and not very good at navigating a maze. In fact the rats were all similar and allocated to each group of students randomly. From what I’ve said, you can probably guess the findings: Students with the supposedly maze bright rats found that their rats could navigate mazes significantly faster!
Reducing experimenter effects The most common ploy is called the double blind technique, in which neither the participants nor the researchers dealing with the participants know the conditions etc. Obviously someone distant from the procedure still needs to know which participants are in which condition so that results can be analysed! This procedure is commonly used in drug testing when genuine medicines are compared to placebos. Remember that on top of this there is the 'data analysis' section, which involves some number crunching. See contents page for details. However, the worksheets provided in lessons should cover this are in sufficient detail so I'll skip notes on this and concentrate on conformity instead. Hope this has not been too heavy a read, I've tried to keep it brief and to the point!
|
