Flashcards in Research Skills 3 Deck (73)

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1

## What are research ethics?

### Refers to a written code of value principles that we use to make decisions about what is acceptable practice in any research project

2

## What ethical code does psychology rely on?

###
BPS code of ethics and conduct (2009)

Code of human research ethics (2011)

3

## What situations may result in ethical considerations?

###
Vulnerable groups (LD, Children, lacking capacity)

Sensitive topics (Ptps sexual behaviour, experience of violence)

Deception

Personal/sensitive and confidential information records

4

## What is informed consent?

###
Involvement of research should be entered into voluntarily, knowingly and intelligently (Koocher & Keith-Spiegel, 1998)

(Israel & Hay, 2006, p. 61):

- researchers need to provide participants with information about the purpose, methods, demands, risks, inconveniences, discomforts, possible outcomes of the research, and how results are disseminated.

5

## When might informed consent not be necessary?

###
Anonymous completion for questionnaires (although content may be sensitive and require prior information.)

Observational research in a public setting.

6

## Types of deception?

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Passive deception (withholding information):

- hypotheses

- purpose

- elements (e.g. priming)

Active deception - misleading participant:

7

## What must be considered in deception before use, and what must be done if deception is used?

###
Depends on nature and seriousness:

Researchers should provide as full information as possible

Researchers must explain any deception at the earliest opportunity

Alternative approaches avoiding deception should be considered in cost-befit context

Ptps likely response needs to be considered

8

## Points that contribute to the integrity of the researcher?

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Whether the researcher has plagiarised

providing paper credit for contributors

Make raw data available for verification (storage)

Transparency

Bias in reporting

9

## BPS guidelines for animal studies?

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Avoid or minimise discomfort

Replace animals with non-sentience whenever possible

Minimise no. of animals used

10

## When would you use an ANOVA (i.e. over a T test)?

###
Compare mean of continuous DV between more than two groups of a single categorical IV

Compare mean of continuous DV between two or more groups on more than one categorical IV

Only ONE continuous DV, have to have categorical IV.

11

## What is GLM?

### General linear model = particular way SPSS does ANOVAs, always means you are doing an ANOVA

12

## Other names for the Dependent variable and the independent variable?

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Dependent = Outcome

IV = Experimental or Factor

13

## Fundamental principle of an ANOVA?

###
So we know the variability of the IV (because we've manipulated it) how much of this variability is accounts for the variability (results) of the dependent variable.

This is the F-ratio

SSr = residual = random variance that you can't explain by you IV

SSm = model = Variance you can explain from you model

A highly significant result will have a larger amount of SSm.

14

## Why is it advantageous to run one ANOVA rather than lots of T-tests?

### All tests are probability based i.e. each time there is a 5%. If you do lots you may make a type 1 error (incorrectly reject null). One test (calculating an F-ratio) reduced this to only one 5% risk.

15

## What are you interested in interpreting when you have one independent variable?

### Only Main effects. NOT interaction.

16

## Assumptions for a one way ANOVA?

###
Independent sampling (not influenced by other)

DV has an interval scale (distance between is equal)

Normally distributed within levels (DV)

Variance needs to be similar within each group. (homogeneity in independent groups, sphericity for repeated measures)

17

## How can you check normal distribution (skewness and kurtosis) in you SPSS output?

### Take the statistic and divide by Std Error, if it is above 1.96 then it is significantly skewed/kurtosed (p

18

## What formal tests are there for normality in SPSS?

### Shapiro wilk, Kolmogorov-Smirnov

19

## If the test for homogeneity of variance in SPSS is significant what does this indicate?

###
They are not homogenous (bad)

Good if non-sig

20

## Two ways to calculate effect size from 1-way ANOVA?

###
Independent groups (manual):

- eta squared (total variance explained)

- Omega squared (better- adjusts for random error)

Repeated measures (can request in SPSS) :

- Partial eta squared (variance uniquely explained by that variable)

- Omega squared

21

## What are pair-wise comparisons? Problems (if not done as a test)?

###
Essentially lots of t tests between the different levels of the IV.

Family-wise error rate is high (lots of 5% unreliability) if you just did lots of t-test

22

## How does a bonferroni post-hoc test work?

### It does pairwise comparison tests but pushes the p value down to a more conservative value so the risk of type 1 error is not as high.

23

## What are planned contrasts?

### When we look at all possible comparisons we could make, decide that we are only interested in comparing.a few levels.

24

## When reporting results of a 1-way ANOVA what is the layout?

### F(*df-model*,*df-error*) = *F-stat*, *p-stat*, *type-of-effect-size-test* = *effect-size-stat*

25

## Layout for reporting pairwise comparisons of a 1-way ANOVA

### Mean difference [95% Confidence interval1, 95% CI2]

26

## Layout for reporting planned contrasts of a 1-way ANOVA?

###
For each contrast (one row in SPSS)

t(df) = *t-stat*, p = *p-value*, r = *effect-size*

27

## What situation is Tukey superior to Bonferroni?

### Tukey is better when making LOTS of pairwise comparisons.

28

## What situation calls for a factorial ANOVA (including 2-way)?

### When there is more than one categorical IV. 2 IVs = 2 way, 3 IV equals 3 way and so on.

29

## Fundamental principle in factorial ANOVAs?

###
Independent Groups: Like a 1 way but the variability for the model is split in 3. One section for IV 1, one for IV 2 and one for IV 1+2.

Repeated Measures: The same but you can discard another chunk that is between factors (so it should be more powerful)

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