general linear model and ANOVA (w8)

Question 1

what does the general linear model assume

Answer 1

that the ‘residuals will be normally distributed
that different statistical tests combine linearly (add together in a simple way)

Question 2

purpose of GLM statistical tests

Answer 2

assess strengths + direction of relationships + differences
strengths of interventions + manipulations

Question 3

what does ANOVA stand for

Answer 3

ANalysis Of VAriance

Question 4

what are ANOVA’s for

Answer 4

categorical differences between:
- different conditions in a study (eg drug v placebo)
- different groups in a study (eg old v young, intervention v control)

Question 5

in t test: how many and what type of predictor and outcome, what is the group and measure

Answer 5

1 categorical predictor (group = IV)
1 continuous outcome ( measure = DV)

Question 6

in ANOVA how many and what type of predictor and outcome, what is the group and measure

Answer 6

1 categorical predictor (group = IV)
1 continuous outcome ( measure = DV)

Question 7

what are the different types of ANOVA

Answer 7

one way, factorial (or multi-way), repeated measures (or within-subjects), mixed

Question 8

in one way ANOVA: how many groups, how many and what type of predictor and outcome, what is the group and measure

Answer 8

3+ groups
1 categorical predictors (group=IV)
1 continuous outcome (measure=DV)

Question 9

in factorial (multi way) ANOVA: how many groups, how many and what type of predictor and outcome, what is the group and measure

Answer 9

2+ groups
2+ categorical predictors (group, sex)
1 continuous outcome (measure)

Question 10

in repeated measures (within subjects) ANOVA: how many groups, how many and what type of predictor and outcome, what is the group and measure

Answer 10

1 group
2+ categorical predictors (intervention, state)
1 continuous outcome (measure)

Question 11

in mixed design ANOVA: how many groups, how many and what type of predictor and outcome, what is the group and measure

Answer 11

2+ groups
1+ categorical predictors (intervention=within, drug=between, sex=between)
1 continuous outcome (measure)

Question 12

what is an interaction between 2 variables

Answer 12

when differences in one variable are affected by differences in another variable

Question 13

what are assumptions in ANOVA

Answer 13

observations are independent (ie from different people, different times)
variances of different groups or conditions should be roughly equal
residuals (unexplained variance or error) will be roughly normally distributed

Question 14

what assumption is made in RM-ANOVA, what do you need to do if you have 3+ groups)

Answer 14

the differences between levels of a variable should roughly equal variance (3+ groups or conditions in a variable, check sphericity)

Question 15

what can post-hoc tests provide

Answer 15

p-values for differences

Question 16

what type of ANOVA is it when one group trained over 4 weeks, each week they took carbs, guarana, caffeine or placebo, measure perception of fatigue before and after training session

Answer 16

repeated measures ANOVA

Question 17

what type of ANOVA is it when one group trained over 4 weeks, each week they took carbs, guarana, caffeine or placebo, 40 men, 40 women, measure perception of fatigue in each group after training session

Answer 17

mixed (within and between) ANOVA

Question 18

what type of ANOVA is it when
each of 4 training groups had carbs, guarana, caffeine or placebo, groups formed separately by sex, 10 people each group, 80 people total
measure perception of fatigue in each group after training session

Answer 18

factorial (multi way) ANOVA

Question 19

what’s a MANOVA for

Answer 19

multiple outcome variables (eg height and weight)

Question 20

what’s ANCOVA for

Answer 20

continuous predictor variable (eg cholesterol)

Question 21

what’s logistic regression for

Answer 21

discrete outcome variables (eg diabetes/not)

Question 22

what’s multivariate regression for

Answer 22

multiple predictor and outcome variables (eg cholesterol, height; diabetes/not, weight)