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research methods and data analysis > General linear model and ANOVA > Flashcards

General linear model and ANOVA Flashcards

1
Q

what is the general linear model?

A
  • Framework for comparing how several variables affect different continuous variables
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2
Q

what does general linear model include?

A
  • correlations
  • t- tests
  • regression
  • ANOVA/ ANCOVA
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3
Q

why does general linear model work?

A
  • because it assumes that the residuals will be normally distributed and that different statistical tests combine linearly
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4
Q

why is it known as linear?

A
  • because different stats tests add together in a simple way
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5
Q

what are the two main purposes of the general linear model?

A
  • strengths and directions of relationships and differences
  • strengths of interactions and manipulations
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6
Q

what do all general linear model tests analyse?

A
  • all analyse variance
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7
Q

what differences do ANOVAs find?

A
  • categorical differences between different conditions or different groups in a study
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8
Q

what are the two special kinds of linear regression?

A
  • ANOVA
  • T test
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9
Q

what is regression?

A
  • statistical test to analyse relationship between a dependent variable (target) and one or more independent variables ( predictor)
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10
Q

what does ANOVA test?

A
  • tests differences between two or more means
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11
Q

how is ANOVA different from a t-test?

A
  • t- test generally used for comparing two means whereas ANOVA used for three
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12
Q

describe the variables of an ANOVA test

A

one categorical predictor (group= IV)
+
one continuous outcome (measure= DV)

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13
Q

what is a one way ANOVA?

A
  • compares the means of three or more independent groups to determine if there is a statically significant difference between the means
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14
Q

how many groups in one- way ANOVA?

A
  • three or more groups
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15
Q

how many variables, predictors and outcomes in one way ANOVA?

A
  • one outcome variable
  • one categorical predictor
  • one continuous outcome
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16
Q

what is factorial (or multi- way) ANOVA?

A
  • used when you’d like to understand how two or more factors affect a response variable and whether or not there is an interaction effect between the factors and the response variable
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17
Q

how many groups in factorial ANOVA?

A
  • two or more groups
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18
Q

how many variables, predictors and outcomes in factorial ANOVA?

A
  • two or more categorical predictor variables (sex, group)
  • one continuous outcome variable(measure)
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19
Q

what is the grid created in factorial ANOVA? can individuals be in more than one group?

A
  • 2 x 2
  • four individual groups
  • each person can only be in one
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20
Q

what is repeated measures ANOVA also known as?

A
  • within- subjects
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21
Q

what is repeated measures ANOVA?

A
  • compares means of three or more groups in which the same subjects show up in each group
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22
Q

how many groups in repeated measures ANOVA?

A
  • one group
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23
Q

how many predictors and outcomes in repeated measures ANOVA?

A
  • two or more categorical predictors
  • one outcome variable (measure)
24
Q

what is mixed ANOVA?

A
  • compares mean differences between groups based on two factors : within and between subjects
25
Q

how many groups in mixed ANOVA?

A
  • two or more groups
26
Q

how many predictors and outcomes in mixed ANOVA?

A
  • one or more categorical predictors
  • one outcome variable
27
Q

what are the three things you should work out before deciding the appropriate test?

A
  • between group variable
  • within group variable
  • levels of variable
28
Q

what does the graph need to have? and why?

A
  • needs to have error bars
  • to show significance
  • how big is the difference relative to the size of error
29
Q

what does a small standard deviation mean?

A
  • low spread
  • data around mean
30
Q

what are the four other different types of test?

A
  • MANOVA
  • ANCOVA
  • logistic regression
  • multivariate regression
31
Q

what is MANOVA?

A
  • used for multiple outcome variables
    e.g., height and weight
32
Q

what is ANCOVA?

A
  • used for continuous predictor variable
    e.g., cholesterol
33
Q

what is logistic regression?

A
  • discrete outcome variances
    e.g., diabetes/ not
34
Q

what is multivariate regression?

A
  • multiple predictor and outcome variables
    e.g., cholesterol, height, diabetes/ not, weight
35
Q

how do you use one way ANOVA on jamovi?

A
  • select one way ANOVA
  • chose mean difference and report significance
36
Q

what type of ANOVA isn’t on jamovi, what do you pick instead?

A
  • Factorial ANOVA isn’t on jamovi
  • just ‘ANOVA’
37
Q

what is mixed ANOVA under on jamovi?

A
  • under repeated measures
38
Q

how do you report one way ANOVA results?

A

F (df1, df2), p value

39
Q

how do you find df1?

A

number of groups - 1

40
Q

how do you find df2?

A

number of values- number of groups

41
Q

what do you run after finding a significant difference among three or more groups/ conditions? what are they?

A
  • run post- hoc tests to see which groups were significantly different from each other
  • they are t- tests but with some corrections applied to the p- values
42
Q

what corrections are applied to post- hoc tests?

A
  • corrections consider multiple comparisons
43
Q

what is interaction ?

A
  • between two variables
  • differences in one variable are affected by differences in another variable
44
Q

what does the interaction speciality depend on?

A
  • your theory
  • how you entered the data into ANOVA
45
Q

how are interactions indicated?

A
  • by a star *
46
Q

what is sphericity?

A
  • variances of the differences between all combinations of related groups (levels) are equal
47
Q

does all data need to be corrected?

A
  • no correction if variability is similar for the conditions
48
Q

what is non- sphericity?

A
  • variances of the differences between all combinations are not equal
49
Q

what changes when you report results after correction?

A
  • degrees of freedom changes
50
Q

what is the assumptions about observations in ANOVA?

A
  • observations are independent e.g., from different people; different times
51
Q

what is the assumption about variance in ANOVA?

A
  • variance of different groups or conditions should be equal
52
Q

what is the assumption about residuals in ANOVA?

A
  • residuals will be normally distributed
53
Q

what are residuals?

A
  • unexplained variance/ error
54
Q

what is the assumption in repeated measures ANOVA?

A
  • differences between levels of a variable should have equal vairance
55
Q

if you have three or more groups/ conditions in a variable in a RM ANOVA what should you check?

A
  • check sphericity

research methods and data analysis (10 decks)

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