PSYCH501 Module 3

an independent variable with a > 2 levels in which participants are randomized into a groups

all differences among the a parameter values

adjusted alpha level that allows researcher to be 100(1-α)% confident that all v confidence intervals have captured their population parameters

used in a one-factor experiment to allow researhcer to exaimine all possible pairwise comparisons of population means; yields a slightly narrower CI than the Bonferroni method

similar to the Tukey-Kramer method, but does not assume equal populatin variance

C_jj, where C_j is a coefficient specified by the researcher for each  

the number assigned to each  in a linear contrast 

a linear contrast that has been divided by the standardizer so that it is a unitless measure

a method of assessing the sources of variability in a one-factor designed where the variability is due to the variance of scores within treatments and the mean differences across treatments

the variance due to mean differences across treatments

variance of scores within a treatment group, describes the variance due to chance and error

describes the proportion of DV variance in the population that is explained by the IV

an adjustment of eta-squared that is less positively biased

used to assess the causal effect of two IV's on the DV as well as the effect of the interaction of the two IV's

a factor with levels to which participants are classified according to some existing characteristic

the effect of one IV averaged across the levels of the other IV

occurs when the effect of factor A is not the same across the levels of factor B

the difference in means at each level of each IV

random samples are taken from two or more different study populations that differ geographically or in other demographic characteristics

comparing the effects of one level of a treatment factor to all other levels of the same treatment factor averaged over the levels of the other treatment(s).

a comparison between the mean in any two cells of a factorial experiment

assesses the source of variability in a factorial design, where the variabiliyt of DV scores is due to: the variance in difference of means across the levels of factor A, the variance in difference of means across the levels of factor B, the variance due to the AB interaction, and the variance of scores within treatments

measure of the proportion of variability due to the effect of one factor in a factorial design where the effects of all other factors has been removed

an adjustment of partial eta-squared that is less positively biased

an experiment that examines the effects of three different factors to provide information about main effects, simple main effects, and interactions (two-way or three-way)

a difference in simple two-way interaction effects 

the difference in means between two levels of any treatment factor in a three-way design

the decomposition of the total variance in a three-fator design

occurs when the levels of a factor are randomly selected from a large set of M possible factor levels

occurs when the levels of a factor are deliberately selected by the researcher and are the only factor levels of interest

a visual representation of a two-factor design in which the means for the levels of one factor are represented by a cluster of contiguous bars and the levels of the second factor are represented by different clusters