Flashcards in Chapter 22 Multi-Level Analysis (625-635) Deck (32)

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1

## Analysis of Variance (ANOVA) (3)

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1. Statistical technique that

2. Compares variances within and between samples

3. In order to estimate the significance of differences between a set of means

2

## Capitalising on Chance (4)

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1. Making too many tests

2. With alpha set at .05

3. On the same data,

4. Hence increasing the likelihood of a Type I error

3

## Within Groups Sum of Squares (4)

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1. Sum of squares

2. of deviations of scores

3. around their sample means.

4. Also: error SS.

4

## Within Groups Variance (3)

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1. Total variance of scores

2. around sample means.

3. Also. error variance.

5

## Between Groups Variance (2)

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1. Variance of sample means

2. around grand mean.

6

## Grand Mean (2)

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1. Mean of all scores in a data set,

2. irrespective of conditions or groups

7

## Total Variance (2)

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1. Variance of all scores in a set

2. around their grand mean

8

## Error Variance (3)

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1. Total variance of all scores

2. from their group means.

3. Also: within groups variance.

9

## F test/ratio (1)

### 1. Statistic giving ratio of between groups to within groups variance

10

## Sum of Squares (1)

### 1. Addition of the squares of deviations around a mean

11

## Variance Ratio Test (1)

### 1. Full name for the test producing the F statistic

12

## Mean Sum of Squares (1)

### 1. Sum of squares divided by df

13

## Between Group Sum of Squares (1)

### 1. Sum of squares of deviations of sample means from the grand mean

14

## Error Sum of Squares (2)

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1. Sum of squares of deviations of each score from its own group mean.

2. Also: within group SS.

15

## Pairwise Comparison (2)

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1. Comparison of just two means

2. From a set of means

16

## Post Hoc Comparisons/Tests (2)

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1. Tests between means, or groups of means

2. Conducted after inspection of data from initial analysis

17

## A Priori Comparisons/Planned Comparisons (2)

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1. Tests of differences between selected means, or sets of means,

2. Which, from prior theory, were predicted to differ

18

## Family-Wise Error Rate (3)

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1. The probability of making at least one Type I error

2. In all the tests made on a set of data,

3. Assuming H0 is true

19

## Error Rate per Comparison (3)

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1. Given the significance level set,

2. The likelihood of a Type I error in each test made on the data

3. If H0 is true

20

## Bonferroni t Tests (3)

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1. Procedure for testing means pairwise,

2. Which involves raising the critical values of t

3. To lower the family-wise error rate

21

## Linear Contrasts (2)

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1. Procedure for testing between individual pairs of means or combinations of means,

2. a priori (i.e. predicted)

22

## Linear Coefficients (2)

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1. Values to be entered into an equation

2. For calculating linear contrasts

23

## Newman-Keuls Post Hoc Test (2)

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1. Post hoc test of means pairwise

2. Safe so long as number of means is relatively low

24

## Tukey's (HSD) Post Hoc Test (3)

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1. Post hoc test of all possible pairwise combinations

2. Appropriate analysis choice with a large number of means

3. Considered conservative.

25

## Tukey's (WSD) Post Hoc Test (1)

### 1. Less conservative post hoc test than Tukey (HSD)

26

## Phi (1)

### 1. Phi statistic for estimating power in ANOVA analyses

27

## Kruskal-Wallis Test (4)

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1. Non-parametric

2. Between-groups

3. Test of difference between several groups

4. (Mann-Whitney is the two-condition equivalent)

28

## Jonckheere Trend Test (3)

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1. Non-parametric

2. Statistical test for the significance of a trend

3. In the dependent variable across unrelated conditions

29

## MANOVA (2)

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1. Statistical procedure using ANOVA

2. On more than one dependent variable

30