Quantitative Data Analysis for Health Research · Independent Samples Repeated Measures k groups:...

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Part I: 14 July 2011

Toronto Rehab

550 University Ave.

Manolo Romero Escobar

http://mixedReviews.wordpress.com

14/07/20111

Quantitative Data Analysis

for Health Research

Your type of question

14/07/20112

Descriptive

Relational

Causal

Your type of design

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Passive-Observational

Quasi-experimental

Experimental

Types of experimental designs

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Type Observation Treatment Observation Treatment Observation

Basic: X O

O

Factorial X(A1B1)

X(A1B2)

X(A2B1)

X(A2B2)

O

O

O

O

Pre-test

Post-test

O

O

X O

O

Solomon Four

Group

O

O

X

X

O

O

O

O

Switching

Replications

O

O

X O

O X

O

O

Crossover O

O

X(A)

X(B)

O

O

X(B)

X(A)

O

O

Longitudinal O...O X O. O...O

Types of control groups

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Placebo Expectancy Wait-list

AttentionNo-

Attention

Sampling and the sampling distribution

Central Limit Theorem Applet

http://www.cs.uic.edu/

~wilkinson/Applets/clt.

html

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Levels of SES

Treatm

en

t C

on

dit

ions

+++

+

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++ ++

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+ ++

Control Emotion Focus Empowrmnt

46

810

12

14

Self

-Est

eem

Treatment Condition

5 10 15 20

46

810

12

14

Resilience)

Self

-Est

eem

Categorical variables

Testing mean differences of a continuous variable

between groups (categorical variable)

Continuous variables

7

Mean contrast & ANOVA

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2 groups: t-test

Independent Samples

Repeated Measures

k groups: ANOVA

One way ANOVA

One-way Repeated Measures

Factorial (e.g. 2x2)

Repeated Measures Factorial

Extensions to the factorial design

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• Levels as in T1, T2, control.

• Factors: Main effects: A, B, C

• Interactions: AB, AC, BC, ABC

Add levels/factors

• Non-random (e.g. Gender) factor

• Sometimes better to use ANCOVA (GLM)

Blocking factor

• Within-Between effects

• Issues with assumptions: homogeneity of variance (sphericity)

• Corrections: Geisser-Greenhouse & Huynh-Feldt.

Repeated measures

factor

ANOVA, ANCOVA, Regression,χ2

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Method Dependent Independent

ANOVA Continuous Categorical

ANCOVA Continuous At least one

categorical and

one continuous

Multiple

Regression (MR)

Continuous

(linear) or

categorical (e.g.,

logistic)

Continuous or

categorical

(dummy coded)

χ2 test of

independence

Categorical Categorical

Parametric Effect Size Indexes

From Kline 2004

Links on the website:

http://mixedreviews.wordpress.com/2011/07/13/quantitative-data-analysis-part-i/

14/07/201111

G*Power 3

http://www.psycho.uni-

duesseldorf.de/abteilung

en/aap/gpower3

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G*Power 3: Mean contrasts

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�One group:

�Difference from constant

� Two groups:

�Two dependent groups, matched pairs

�Two independent groups

�Many groups:

�ANOVA: One-way (one independent variable)

�ANOVA: Main effects and interactions (two or

more independent variables)

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Exercise 1: t-testt-test: Independent

samples

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� Calculate sample size with

the parameters presented

� Plot sample size (y axis) as

a function of effect size

(use values of d from .2 to

.8)

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Tota

l sam

ple

siz

e

Exercise 2: F test

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DV: Self Esteem

Treatment

Groups

mean sd n

Control 7.63 1.50 40

Emotion Focus 11.43 2.11 40

Empowerment 9.73 1.75 40

SES Groups mean sd n

low 8.84 2.36 32

medium 9.66 2.32 59

high 10.28 2.34 29

� One way ANOVA omnibus

test

� Estimate the effect size for

each IV groups

� With power of .80

determine sample size

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