Module 6

Question 1

Dummy coding

Answer 1

Most straightforward approach to including an independent variable with J categories in a linear model is to use dummy coding

Dummy coding - independent variable with J levels is broken down into J-1 separate binary dummy variables, each of which is coded to equal either 0 or 1

Question 2

Reference category

Answer 2

one of the J levels of the IV is chosen as the reference category - reference category is assigned a value of 0 on each of the dummy variables

control is usually the reference category

Question 3

what do we want our statistical model to do?

Answer 3

represent how variation in the dependent variable is a function of the 5 category independent variable

Question 4

Slope parameter of dummy variable

Answer 4

Each dummy variable has its own slope parameter - difference between mean of reference category and mean of other category

B1d1+B2d2+B3d3

Question 5

B0 dummy variable

Answer 5

Population mean of the reference categorry

Question 6

Error term dummy variable represents what

Answer 6

Because not every participant in the reference category has the same value as the population mean

Question 7

Confidence intervals around each dummy variable represent what?

Answer 7

Because the slope coefficient estimate of the d1 variable is a point estimate of the difference between the population mean of the rhyming condition and the population mean of the counting condition, then the interval [-2.90, 2.70] captures the population mean difference with 95% confidence

Question 8

How to calculate estimated error term

Answer 8

subtract predicted mean from actual value

= score - mean of that group

Question 9

What does i index

Answer 9

participant ID

Question 10

How to calculate SS residual

Answer 10

get residual for each participant (score - predicted), square it and add them all up

Question 11

How to calculate SS model

Answer 11

Predicted mean of the group - sample mean of the dependent variable (grand mean), squared, summed

Question 12

What is SS model

Answer 12

variability in the model

Question 13

R^2

Answer 13

= eta squared = 1-(SSredid/SStotal) = SSmodel/SStotal

Question 14

If null is true what should the linear slope parameters be equal to?

Answer 14

Eachother and 0
B1=B2=B3=0

Question 15

MS model

Answer 15

SS Model/df model

Question 16

MS Residual

Answer 16

SS residual/df residual

Question 17

F statistic

Answer 17

MS model/MS residual

Question 18

APA style one way anova

Answer 18

“The overall proportion of variance explained by the linear model, R2 = .45, was significant, F (4, 45) = 9.09, p < .001, indicating that the number of words recalled significantly varied across the five conditions representing different levels of depth of processing

Question 19

Significant result on ANOVA says what?

Answer 19

only indicates that at least one population mean is unlikely to be unequal to the
other population means.

Question 20

Planned comparisons

Answer 20

t-tests are valid if a researcher has explicitly and transparently planned at the beginning of the study to compare the mean of the reference category with the means of the other categories.

Question 21

Planned comparisons reporting

Answer 21

“Because the dummy variables in the linear model were defined a priori, the corresponding ttests represent planned comparisons. The rhyming mean (M = 6.90) did not significantly differ from the counting mean (M = 6.90), t (45) = 0.07, p = .94. But the adjective mean (M = 11.00) was significantly different from the counting mean, t (45) = 2.88, p = .006.”
Etc. for the t-tests for the remaining dummy variables

Question 22

ANOVA model assumptions

Answer 22

1. Independent observations
2. Normally distributed errors
3. Homogeneity of variance

Question 23

How to assess assumption of normally distributed errors

Answer 23

examine the residuals from the estimated model

• strong kurtosis would violate this error

Question 24

How to evaluate the homogeneity of variance assumption

Answer 24

Look at sample standard deviations

Dont want any to be like twice another one

but equal sample sizes may protect against unequal SDs