statistical power

Question 1

whats the most commonly used inferential statistical method

Answer 1

hypothesis test

Question 2

whats does the hypothesis test begin with

Answer 2

a null hypothesis

Question 3

whats the purpose of the hypothesis test

Answer 3

to rule out chance as an explanation of the results

Question 4

what does the outcome of a hypothesis test depend on

Answer 4

the sample size

Question 5

what happens if you increase the sample size of a hypothesis test

Answer 5

increases the likelihood of obtaining a significant result

Question 6

what is recommended that researchers provide when reporting a statistically significant effect

Answer 6

an independent measure of effect size

Question 7

type 1 error

Answer 7

rejecting the true hypothesis

Question 8

type 11 error

Answer 8

accepting a false hypothesis

Question 9

what is statistical power

Answer 9

the probability of correctly identifying an effect

-rejecting a false null hypothesis

Question 10

when would researchers attend to power

Answer 10

at the design stage

Question 11

what can power analysis be used for

Answer 11

to calculate the minimum sample size required to accept the outcome of a statistical test with a particular level of confidence

Question 12

practical significance

Answer 12

a result or treatment that is large enough to have value in practical application

Question 13

what is needed for practical significance

Answer 13

the size of the effect

Question 14

what is a statistically significant result

Answer 14

one thats unlikely to be due to chance

Question 15

what is a practically significant result

Answer 15

one thats meaningful in the real world

Question 16

effect size

Answer 16

the measured magnitude of a treatment effect or relationship that is not influenced by factors such as sample size

Question 17

what is the estimation of effect size essential for

Answer 17

• practical significance
• desired sample size
• comparison across different studies

Question 18

the d family

Answer 18

effect sizes assessing the difference between groups on continuous variables

Question 19

what are effect sizes for continuous variables

Answer 19

standardised mean differences

Question 20

how is effect size for continuous variables calculated

Answer 20

subtract mean of one group from the other and divide result by the SD of population
*the bigger the score the bigger the effect

Question 21

cohens d

Answer 21

the size of the mean difference between two treatments can be standardised by measuring the mean difference in terms of SD

Question 22

what does d mean in cohens d

Answer 22

sample mean difference divided by sample SD

Question 23

what does d=2 in cohens d indicate

Answer 23

mean difference is twice as big as SD

Question 24

what does d=0.50 indicate in cohens d

Answer 24

mean difference is half as large as the SD

Question 25

the r family

Answer 25

effect sizes measuring the strength of a relationship between 2 or more variables

Question 26

what are egs of the r family

Answer 26

* correlation coefficients * standardized regression weights * regression measures of variance explained

Question 27

context of interpretation of effect sizes

Answer 27

small effects can be important if they trigger big consequences, accumulate into larger effects or lead to technological breakthroughs and new discoveries

Question 28

contribution to knowledge - interpreting effect sizes

Answer 28

* interpret results in context of current evidence | * does the observed effect differ from what others have found

Question 29

whats a small standardised mean difference for cohens criteria

Answer 29

.20

Question 30

whats a medium standardised mean difference for cohens criteria

Answer 30

.50

Question 31

whats a large standardised mean difference for cohens criteria

Answer 31

.80

Question 32

whats a very large standardised mean difference for cohens criteria

Answer 32

1.30

Question 33

whats a small correlation for cohens criteria

Answer 33

.10

Question 34

whats a medium correlation for cohens criteria

Answer 34

.30

Question 35

whats a large correlation for cohens criteria

Answer 35

.50

Question 36

whats a very large correlation for cohens criteria

Answer 36

.70

Question 37

how to increase statistical power - effect size

Answer 37

increasing effect size increases power

Question 38

how to increase statistical power - alpha level

Answer 38

* usual value p= 0.05 | * increasing alpha increases power

Question 39

how to increase statistical power - sample size

Answer 39

increasing sample size increases power

Question 40

what are the 4 main parameters of power analysis

Answer 40

1. effect size 2. sample size 3. alpha significance criterion 4. power of the statistical test

Question 41

how to obtain the effect size for power analysis - a literature review

Answer 41

* estimate the effect size based on published studies similar * relevant values are not entirely clear

Question 42

how to obtain the effect size for power analysis - a pilot study

Answer 42

* rough estimate of effect size | * info extracted from a small sample is limited and bias

Question 43

how to obtain the effect size for power analysis - cohens reccomendations

Answer 43

*small effects - large effects reccomendations