Flashcards in Analysing variance and analysis of repeated measurements Deck (11)

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1

## What is the principle behind analysis of variance?

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to partition the total variability of a set of data into components due to different sources of variation

systematic differences between the group means and

the variations between individuals within each group

2

## What is the null hypothesis in one-way analysis of variance?

### The is no difference been the groups and the test compares the observed variation between the groups with that elected from the observed variability between subjects

3

## What are the assumptions underlying ANOVA?

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the samples come from normally distributed populations with the same standard deviation

normality of residuals

independence

4

## What is the problem of making multiple comparisons?

### gives a high probability of a finding a significant difference just by chance

5

## What is the bonferroni method?

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a method of manual multiple testing

it is fine for up to 5 comparisons but is highly conservative

it adjusts the p value to account for multiple testing

6

## Describe Tukey's HSD

### most sensible choice if you wish to consider all comparisons

7

## Describe Dunnett's

### most sensible choice when you are only interested in comparing one group (e.g control) to each of the other groups. More powerful than Tukey's in this situation

8

## Describe Fisher's LSD

### not generally recommended. does not take multiple comparisons into consideration

9

## What is different about the analysis of repeated measurements?

### observations on the same subject just have some relationship between them, and are very likely to be correlated to each other. Data points are not independent

10

## What are the problems with point by point analysis of repeated measurements?

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ignores the correlation between successive observations from the same individual

may conceal important features of the data

causes a multiple testing problem

ignores the continuous nature of the underlying process

11