Week 3: ANOVAs Flashcards

1
Q

what type of numbers do ANOVAs use?

A

ANOVAs use the F statistic

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2
Q

if variance between samples is small, F will be ______

A

small

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3
Q

if variance within samples is small, F will be ______

A

large

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4
Q

ANOVAs will compare

A

3 or more groups (= levels of 1 IV)

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5
Q

One-way ANOVA definition

A

one IV with 3+ levels: dry needling vs massage vs sham dry needling; separate groups for each intervention

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6
Q

One-way repeated measures ANOVA

A

one IV with 3+ levels: dry needling vs massage vs sham dry needling; everyone gets all interventions

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7
Q

Two-way ANOVA

A

two IVs: Dry needling vs sham dry needling AND stretching vs no stretching; separate groups for each intervention

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8
Q

Two-way repeated measures ANOVA

A

two IVs: Dry needling vs sham dry needling AND stretching vs no stretching; everyone gets ALL combination of IVs

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9
Q

Mixed Model ANOVA

A

Two IVs: dry needling vs sham dry needling AND time (pretest, 4-weeks post, 8-weeks post); two intervention groups, but all participants are measured at all points in time

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10
Q

Total Variance in a One-Way ANOVA is what two groups

A

between groups and within groups

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11
Q

between groups variance is

A

differences between means

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12
Q

within groups variance is

A

between subjects error variance

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13
Q

comparison of group means

A

ANOVA looks at distance of each group mean from the grand mean (total group)

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14
Q

Interpreting F statistic

A

“omnibus test”; overall; nonspecific; tell you a difference exists, but will not specify WHERE

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15
Q

Multiple comparison tests will tell you ________ the difference exists

A

WHERE the difference exists; if null is not rejected, no multiple comparison tests are needed

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16
Q

effect size =

A

how much the IV affected the DV

17
Q

effect size indices for the ANOVA

A

eta squared (n^2) and Cohen’s f

18
Q

small effect size: n^2

A

.01

19
Q

medium effect size: n^2

A

.06

20
Q

large effect size: n^2

A

.14

21
Q

small effect size: f

A

.10

22
Q

medium effect size: f

A

.25

23
Q

large effect size: f

A

.40

24
Q

designs for repeated measures has what characteristic

A

the same people in each level of the IV

25
Q

simplest example of a repeated measures design is

A

one-way repeated measures design

26
Q

true/false: subjects act as their own controls in designs for repeated measures

A

true

27
Q

multiple comparison tests are used to

A

determine “where” difference is after using ANOVA; also called “pairwise comparisons”

28
Q

what are the 2 different strategies for multiple comparison tests

A

post-hoc and planned comparisons

29
Q

post-hoc info

A
  • performed after ANOVA (only if significant)
  • most common
  • test every difference, therefore are “exploratory”
30
Q

planned comparisons info

A
  • performed instead of ANOVA (a priori)
  • focused only on specific comparisons
  • you won’t see this used very often
31
Q

types of multiple comparison tests for independent groups

A
  • Fisher’s least significant difference
  • Duncan multiple range test
  • Newman-Keuls Method
  • Tukey’s honestly significant difference
  • Bonferroni t-test
  • Scheffé’s comparison
32
Q

Fisher’s Least Significant Difference information

A

essentially unadjusted t-tests (LSD)

33
Q

Tukey’s Honestly Significant Difference info

A

“middle of the road” in terms of risk and most commonly used

34
Q

Bonferroni t-test info

A

simply divides alpha by # of comparisons (also called Bonferroni adjustment or correction

35
Q

multiple comparison test for Repeated Measures

A

LSD, Sidak, Bonferroni correction

36
Q

LSD definition

A

unadjusted paired t-tests

37
Q

Sidak definition

A

adjusted, but good balance of type 1 and type 2 error protection; MOST COMMON

38
Q

Bonferroni correction definition

A

divides alpha by # of comparison

39
Q

We only need Multiple Comparisons IF there is a _______________ in the omnibus test

A

significant difference