In the repeated-measures t statistic, the value of the estimated standard error in the denominator is computed entirely from the sample data

False

In a repeated-measures study comparing two treatments with a sample of n=15 participants, the researcher measures two scores for each individual to obtain a total of 30 scores. The repeated measures t statistic for this study has df=29

False; The 30 scores are used to compute 15 different scores: df=14

If a set of n=16 difference scores has a mean of MD=4 and a variance of s(sqd)=36. Cohen's d for this sample is d=4/6

True

A repeated measures study with a sample of n=16 participants produces a repeated measures t=2.00. If effect size is measuring using r(sqd), then r(sqd)=4/20.

False; r(sqd)=4/19

High variance for a sample of difference scores indicates that the treatment does not have a consistent effect.

True

If other factors are held constant, the higher the variance is for a sample of difference scores, the lower the likelihood of rejecting the null hypothesis

True

A repeated measures study would not be appropriate for which situation?

A researcher would like to compare individuals from two different populations. (Two difference populations will require two different samples).

A repeated measures study and a matched subjects study are both used to compare two treatments. If each study uses a total of 30 participants, then what are the df values for the two studies?

repeated measures df=29

matched subjects df=14 (study uses 15 matched pairs)

matched subjects df=14 (study uses 15 matched pairs)

A repeated measures exp. & an independent measures exp. both produce t statistics with df=20. How many individuals participated in each experiment?

n=22 for independent measures (2 groups, each n-11

n=21 for repeated measures (1 group n=21

n=21 for repeated measures (1 group n=21

In general, what characteristic of the difference scores are most likely to produce a significant t statistic for the repeated-measures hypothesis test?

a large number of scores & a small variance

What's indicated by a large variance for a sample of difference scores?

a consistent treatment effect & a high likelihood of a significant difference

A large variance indicates that the difference scores are widely scattered.

A large variance indicates that the difference scores are widely scattered.

A researcher is using a repeated-measures study to evaluate the difference btw two treatments. If there's a consistent difference btw the treatments then the data should produce

a small variance for the difference scores & a small standard error

Consistent difference scores produce a small variance & less error

Consistent difference scores produce a small variance & less error

For which of the following situations would a repeated-measures design have a substantial advantage over an independent measures design

few subject available & individual differences are large

RMD: requires few participants & removes the ind dif

RMD: requires few participants & removes the ind dif

Which of the following would have little or no influence on effect size as measured by Cohen's d or by r(sqd)?

Increasing the sample size

sample size has little or no influence on measures of effect size

sample size has little or no influence on measures of effect size

Which of the following is not true of a repeated-measures design compared to an independent measures design?

The repeated measures design is less likely to reject the the null hypothesis.

RMD typically has a smaller standard error & is more likely to detect a real treatment effect.

RMD typically has a smaller standard error & is more likely to detect a real treatment effect.