Flashcards in Chapter 10 Deck (25):
Analysis of variance (ANOVA)
a statistical procedure that uses the F-ratio to test the overall fit of a linear model. In experimental research this linear model tends to be defined in terms of group means and the resulting ANOVA is therefore an overall test of whether group means differ.
a correction applied to the α-level to control the overall Type I error rate when multiple significance tests are carried out. Each test conducted should use a criterion of significance of the α-level (normally .05) divided by the number of tests conducted. This is a simple but effective correction, but tends to be too strict when lots of tests are performed.
a version of the F-ratio designed to be accurate when the assumption of homogeneity of variance has been violated.
if you connected the means in ordered conditions with a line then a cubic trend is shown by two changes in the direction of this line. You must have at least four ordered conditions.
a non-orthogonal planned contrast that compares the mean of each group (except first or last depending on how the contrast is specified) to the overall mean.
Difference contrast (reverse Helmert contrast)
a non-orthogonal planned contrast that compares the mean of each condition (except the first) to the overall mean of all previous conditions combined.
Eta squared (η2):
Experimentwise error rate
the probability of making a Type I error in an experiment involving one or more statistical comparisons when the null hypothesis is true in each case.
Familywise error rate
the probability of making a Type I error in any family of tests when the null hypothesis is true in each case. The 'family of tests' can be loosely defined as a set of tests conducted on the same data set and addressing the same empirical question.
the variance within an entire set of observations.
a weighted version of the
a non-orthogonal planned contrast that compares the mean of each condition (except the last) to the overall mean all subsequent conditions combined.
analysis of variance conducted on any design in which all independent variables or predictors have been manipulated using different participants (i.e. all data come from different entities).
Omega squared, ω2
means perpendicular (at right angles) to something. It tends to be equated to
comparisons of pairs of means.
a set of comparisons between group means that are constructed before any data are collected. These are theory-led comparisons and are based on the idea of partitioning the variance created by the overall effect of group differences into gradually smaller portions of variance. These tests have more power than
a contrast that tests for trends in the data. In its most basic form it looks for a linear trend (i.e. that the group means increase proportionately).
a set of comparisons between group means that were not thought of before data were collected. Typically these tests involve comparing the means of all combinations of pairs of groups. To compensate for the number of tests conducted, each test uses a strict criterion for significance. As such, they tend to have less power than planned contrasts. They are usually used for exploratory
if the means in ordered conditions are connected with a line then a quadratic trend is shown by one change in the direction of this line (e.g. the line is curved in one place); the line is, therefore, U-shaped. There must be at least three ordered conditions.
if the means in ordered conditions are connected with a line then a quartic trend is shown by three changes in the direction of this line. There must be at least five ordered conditions.
a non-orthogonal planned contrast that compares the mean in each condition (except the first) to the mean of the preceding condition.
a non-orthogonal planned contrast that compares the mean in each condition to the mean of either the first or last condition depending on how the contrast is specified.
a number by which something (usually a variable in statistics) is multiplied. The weight assigned to a variable determines the influence that variable has within a mathematical equation: large weights give the variable a lot of influence.