Research Methods Flashcards

(30 cards)

0
Q

What is related data

A

Comparison of two sets of scores from the SAME partcipants

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1
Q

What is independent data?

A

Comparison of two sets of scores from DIFFERENT participants

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2
Q

What is nominal, ordinal and interval/ratio data?

A

Nominal - data collected in categories that can’t be placed on a scale eg those that conformed and those that didn’t
Ordinal - more about order, A ordinal variable, is one where the order matters but not the difference between values.
Interval - remember–interval scales not only tell us about order, but also about the value between each item
Ratio - can never be a zero. Eg height not difference in height.

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3
Q

If it is a test of correlation, what is the test?

A

Spearmans

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4
Q

Sample tests

A

Independent. Related
Nominal. Chi squared Sign test
Ordinal. Mann Whitney. Wilcoxon
Interval/ratio T test. T test

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6
Q

A difference is significant if it is unlikely to be due to chance ( if the null hypothesis were true)

A difference that would occur by chance less than 5 % is…

A

…deemed significant

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6
Q

What is an alternative hypothesis?

A

Predicts a difference

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8
Q

Instead of referring to percentages statisticians refer to p.values - % = p values.
So, if a difference would occur by chance less than 5% of the time then…
If a difference would occur by chance less than 1% of the time then…

Whether a difference is significant depends on what 2 things..

If the difference is significant we do what?

A

…it is significant by p>0.05 - the chance of making a type 1 error is 5%

…it is significant by p>0.05

Sample size
Size of the difference

We reject the null hypothesis and accept the alternative hypothesis

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9
Q

What is difference 1 tailed or 2 tailed hypothesis?

A

1 tailed = When the theory predicts that the difference will be in a particular direction - Used when previous research suggests a direction
2 tailed = non directional - different theories make different predictions - used when previous research is contradictory or there is no previous research.

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10
Q

Type 1 error..

Type 2 error..

A

False positive
Claiming a difference is significant when it’s not
More likely when lenient

False negative
Claiming a difference is not significant when it is
Likely when stringent

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11
Q

1) Spearman’s: When using Spearman’s, you are testing for a correlation between two sets of scores - how does it work?
2) Wilcoxon: when using Wilcoxons test you have 2 sets of scores from the same participants.

A

When using Spearman’s you are testing for a correlation between two sets of scores, The calculated value is the correlation coefficient (i.e., a value between -1 and +1) On the table below the p. values and levels of significance are given across the top and N (the number of pairs of scores) down the left hand side.
In the case of this test, the calculated / observed value has to be equal to or more than the critical value (ignoring whether the correlation is positive or negative).

WILCOXON:

When using Wilcoxon’s you have 2 sets of scores from the same. On the table below the p. values and levels of significance are given across the top and N (the number of pairs of scores) down the left hand. In the case of this test, the calculated / observed value has to be equal to or less than the critical value.

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12
Q

Mann - Whitney: When using a Mann-Whitney test you have scores from two separate groups of participants so there may be unequal numbers.

A

You will be given a table of either critical values of 1 tailed pr 2 tailed tests at p<0.05 depending on what you need. On the table, the left hand column and the top row indicate the number of participants in each condition. The critical value can be calculated by reading down and across from N= how many ppts. If the calculated value is lower than the critical value, so the difference is significant, we can reject the null hypothesis.

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13
Q

Chi-sqaured: The data used for chi-squared test is in the form of frequencies in catorgaries. Imagine an observational study of drivers in which you counted how many males and females wore seat belts or not.

A

When using chi-squared, one needs to know the degrees of freedom. The question to ask is; given that you know the column and row totals in the table of data, how many of the actual frequencies do you need to know to work out the rest?

You are given the calculated/observed value. You are also given a table of degrees of freedom down the first row and level of significance are across the top. Using the standard level of significance (0.05) we can read down to find the critical value for a 2-tailed test, (always two tailed!!!) and along for the DF (degree of freedom) which you are also given. - The observed/calculated value has to be equal to or higher than the critical value.

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14
Q

Ranking data..

A

If a subjective scale is used, then the data is at the ordinal level…

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15
Q

What is qualitative data?

What is quantitative data?

Methods of qualitative data?

What are two options in qualitative data analysis?

A
  • Qualitative data comes in non-numerical form e.g. a description of a clinical case.
  • Quantitative data comes in the form of numbers i.e. you count or measure something.
  • Interviews - (especially un-structured involving open questions) and observations (especially unstructured and participant observation)
  • 1) Converting qualitative data into quantitative data, often using in interviews. - Dunbar & Waynforth analysed the content of personal ads to identify whether males and females offered or asked for different qualities in romantic partners. The original advertisements were the qualitative data.
    2) Extracting information without conversion into quantitative data. Freud gave a detailed account of a single patient in his study of Little Hans.
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16
Q

What is an advantage and disadvantage of using qualitative data?

A

1) ADVANTAGE: The main advantage claimed for qualitative data is that it has a greater validity than quantitative data. The central idea is that qualitative data is more true to life. hence ‘real’, than quantitative data. e.g. In a study of attachment interviews using open questions would enable ppts to talk in their own words about their experiences, so aspects of their experience that the researcher would be unable to anticipate.
2) A disadvantage of qualitative data is subjectivity and bias e.g. Rosenhan - his students reported an overwhelming sense of dehumanisation, severe invasion of privacy and boredom while hospitalized however the problem here is that Rosenhan and his colleagues were already critics of the psychiatric system, which might have made them biased in their observations. With no systematic data collection, they could have ‘cherry- picked’ the worse behaviour, interpreted the staff’s actions in negative ways and ignored the stresses that the staff were under. A different researcher could do the same observation and arrive at a completely different account of what life was like in such a hospital.

17
Q

Two methods of analysing qualitative data?

A

1) Content analysis - The data analysis is the actual conversion of the qualitative data into the categories. In other studies this might involve scoring e.g. the amount of stress in different jobs from diaries. This requires you to identify, in advance, the categories / variables which get counted. Content analysis is used when you have a hypothesis to test, i.e., in an area of research where there is a clear theory to test and measurable variables identified

2) Thematic analysis - The aim of thematic analysis is to identify patterns/ themes within qualitative data and is used to analyse data from bodies of text, such as interviews, newspapers, articles etc.
This is often used when it is not obvious, in advance, what categories could be used in a content analysis.
This identifies categories, but does not count instances within categories.
It identifies themes, which may be used in subsequent research.
Thematic analysis is used in less well researched areas, where it is hard to know in advance what theories to test and which variables to measure

18
Q

Theoretical and Inductive analysis..

What is the difference?

A

In theoretical analysis a theory guides the analysis e.g. in Dunbar’s content analysis his evolutionary theory of sex differences tells us the categories. In inductive analysis a theory only emerges from the data after analysis.

19
Q

What is the defintions of the following words?

1) Reliability
2) Validity
3) Test re-test reliability
4) Spit half reliability
5) Inter-rater observer reliability
6) Intra-rater observer reliability

A

1) Consistency or sameness of a method, measure of researcher.
2) Truth/ accuracy of a method or measure
3) Similarity of two sets of scores taken on different occasions.
4) Similarity of two sets of scores from dfferent halves of a quesitonnaire.
5) Similarity of ratings made by different observers
6) Similarity of ratings made by the same observer.

20
Q

What is the defintions of the following words?

1) Experimental realism
2) Ecological validity
3) Population validity
4) Standardisation
5) Randomisation
6) Correlation

A

1) The extent to which ppts are engaged in and take seriously the experimental task
2) The extent to which the results of a study generalise to other contexts.
3) Extent to which the results of a study generalise to other people, apart from the sample used.
4) Process of making everything the same in a study in some relevant way.
5) Alternative to standardisation for controlling extraneous variables in a study.
6) Statistical measure often used to test reliability of a measure

21
Q

What is the defintions of the following words?

1) Face validity
2) Concurrent validity
3) Predicitive validity

A

1) Extent to which a way of measuring something looks valid.
2) Extent to which a score is similar to a score on another test that is known to be valid.
3) Extent to which a score predicts future behaviour.

22
Q

Validity is to do with truth…

1) What is External validity?
2) What is Internal validity?
3) What are the threats to validity?

A

1) External validity:
- Ecological validity, Population validity, Temporal validity.

2) Internal validity:
- Operationalisation ( does the the study validly measure/manipulate the variables?)
- Control - are extraneous variables controlled?
- Experiemental validity.

4) -Threats:
- Demand characteristics - participants who know they are in a study may guess what the study is about and change their behaviour.
- Social desirability effects - participants may be behave/ respond in socially acceptable ways, either to look good to the research or to measure themselves.
- Order effects - what particpants experience earlier in the study may affect their behaviour later in the study e.g. fatigue.
- Hawthorne effect - ppts who know hey are in a study may try harder than they would in everyday life.

23
Q

How to improve external validity?

A

One way to improve external validity is by repeating or replicating the study. This could be done with a completely different set of participants to test whether the first set of results has population validity. If the study was a lab experiment, the same hypothesis could be tested in a different environment such as a field experiment: This would test the experimental/ecological validity of the first experiment. A final way of improving the e validity, would be to repeat the study years later which would test the temporal validity of the first study.

24
Q

How to improve internal validity?

A

Internal validity refers to how accurately a test or measuring instrument measures what it says it measures

Internal validity can be improved by ensuring that extraneous variables are controlled. The aim of this is to ensure that there are no differences between conditions apart from the independent variable. This allows researchers to test the cause and effect relationship.
Ideally, studies should also have experimental validity i.e. realism. In Loftus study, ppts may not have acted as natural as they would of in a real-life situation.
The best way to improve validity is in advance i.e. by conducting a pilot study in which problems, such as extraneous variables, can be identified and eliminated.

Concurrent validity involves assessing how closely the scores on the happiness questionnaire match a different measurement of happiness obtained from the same participants, for example from family/teacher reports
 Content validity involves asking experts in the field to check the content of the questionnaire to see how accurately it measures happiness
 Face validity is less rigorous and involves looking at the questions to see if they are genuinely asking about happiness

25
Reliability of measurement can be improved by a pilot study. How?
- Materials should be tested to ensure that they yield reliable results from participants i.e. by measuring test re-test and split-half reliability. This should aim to ensure question are not affected by irrelevant factors. - Researchers should be trained to ensure that they are reliable over time for an individual ( to ensure intra-rater reliability) and with each other across a team to ensure inter-rater/observer reliability. This should eliminate inconsistencies in ratings and observations.
26
SAMPLING 1) What does 'population' refer to? 2) A sample is representative if... 3) To generalise is to... 4) Three sampling methods?
1) Population refers to those who the study is about and who the results apply to 2) ... if in the sample, you have people who are typical of the population. 3) To generalise is to claim that what is true of the sample is also true of the population 3) Random- involves the use of a sampling population/frame i.e. a list of possible particpants from whom the actual sample is chosen via some unbiased mechanism e.g. a computer programme so that all members of the sample have an equal chance of being picked. - Opportunity sampling - involves using whoever is available for the research e.g. patients in therapy, students on a course. - Volunteer - involves asking volunteers by publicizing the research where the target audience will see it
27
SAMPLING 1) What are three sources of bias? 2) What is stratified sampling? 3) What are the strengths and limitations of stratified sampling?
1) a) Deliberate or unwitting bias by the researcher in selecting particpants - a researcher may choose a ppts who he believes will give him results that support his hypothesis. b) The use of unrepresentative sampling populations from which samples are taken - If just on one country, it might not be representative of other cultures. c) Chance, or random error, when taking samples, which is more likely with small samples. - when taking random samples it is possible to get an unrepresentative sample just by chance. This can happen in any random sample though it if more likely to occur if a small sample is being chosen. This can be addressed by the use of stratified sampling/ 2) Stratified sampling - divide the sampling frame into groups to be represented in the sample. Sampe randomly from within these groups. Then if a sampling frame is unavailable,.... ..... draw up quotas to be represented, then recruit volunteers till quotas are full. 3) Stratified sampling eliminates the possibiliy of the very unrepresentative samples that can be produced by random sampling. HOWEVER they are expensive to run - - Quota smapling also improves the likelihood that the sample is representative by ensuring that the proportions of each strata in the sample are representative. HOWEVER, there are problems with using volunteers - you will get a certain e.g. in a studies of the impact of attachment few very bad parents volunteer leading to a bias sample.
28
ETHICS 1) What is informed consent? - What should a consent for include? 2) What is the right to withdraw? 3) What is debriefing? 4) How should children be protected?
1) Informed consent - participants should give informed consent. i.e. be made aware of anything that might affect their willingness to particpate. This should include an information sheet about the study, how ethical issues will be dealt with and a declaration of consent. - ---The main aim is to acquire informed consent, i.e., participants are aware of anything that might affect their willingness to participate a) Information sheet about the study * Statement of purpose of study, insofar as this needs to be revealed * What participants will be asked to do, i.e, procedures of the study, in so far as these need to be revealed * This needs to be carefully considered, ensuring that not too much, too little or misleading information is given b) How ethical issues will be dealt with * How anonymity and confidentiality will be ensured * Assurance about participant’s right to withdraw c) Declaration of consent * Include a declaration form for participants to tick and sign, e.g., 2) The right to withdrawal should be clear at the onset of the study i.e. in the consent form. Participants also have the right to withdraw their data retrospectively i.e. after the study. 3) A debriefing should provide participants with any necessary information to complete their understanding of the nature of the research and monitor any unforeseen negative effects or misconceptions. It should include: a) Preliminaries- thanks! * Thank participants for taking part. b) Procedure- completing understanding of the study * Clarify the aim of the study, including anything they need to know to complete their understanding of the study (i.e. anything they wouldn’t have been told when giving consent). c) Ethics- dealing with remaining issues * Ask if they have any questions. * Researchers should ‘identify any unforeseen discomfort, distress or other negative effect of the research’. * Remind participant of their right to withdraw (retrospectively) and to insist that their personal data is destroyed. 4) Children under 16 cannot give their own consent. A parent can give consent on their behalf. In a school setting, children have to give their own consent as well as the head/teacher.
29
STRUCTURE OF A PSYCHOLOGICAL REPORT. What should it include?
1) Contents 2) Title - clear idea of what the research is about which may include naming the theory of the variables 3) Abstract - a summary of the key points of the research with a list of key terms which is often provided separately. The abstract and list of key terms allow researchers to quickly decide if the research is of interest to them. 5) Introduction to background of the study including key issues and debates and relevant studies. ( the funnel technique should be used so that you start with general material then funnel down to more specific research/theories 6) Hypothesis - a hypothesis should be written before research is conducted so that the researcher does not change it later to match their results if they were different to what they expected 7) Method/procedure - gives a clear account of how the study was conducted - this allows replication of the study and therefore findings can be checked should include - method and technique - design - variables - sampling method - materials - procedure - controls e.g. counterbalancing - ethical issues 8) Results - including descriptive statistics (written account of findings, graphs and tables e.c.t) and inferential statistsics ( details of statistical test). It is crucial to identify a statistical test in advance so that u ensure there is an appropriate stat test that can used 9) Discussion of strengths and weaknesses e.g. reliability, validity and generalisability and possible improvments for future research. They may also include practical applications. 10) References - alphabetical list of sources 11) Appendices includes - consent form - lengthy instruction sheet - original materials - raw data (made anonymous) - debriefing form
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Standard deviation...
A higher standard deviation is showing that the scores are more spread out in this condition. Hence, there was more variation in this condition - e.g. if this condition was for the use of brief CBT, then it implys that the therapy may have been more effective for some than others.