Statistics: What do I need to know?

• What are Chi squares, t-tests, ANOVA, correlations and regressions?

• How do I know if the researchers used the correct statistical tests?

How do statstics relate to an indivudal participant

Difference between climate and weather

Can predict exactly what this person will do!

Participants: 65 Pregnant Adolescents Participants: 65 Pregnant Adolescents in Teen Parent Programsin Teen Parent Programs

•Means: age: 16.12, GPA: 2.04, age/grade lag: .17, Grade: 10.8, FOB/MOB age difference: 3.17 year •Percentage: AA (13%), Hispanic (42%), Caucasian (45%).

•Refusal rate: 2%

•Attrition: 6% (fetal demise, diagnosis of CA)

•7 Sites: Relationship of demographics to school attendance: site, ethnicity, SES, age, grade, GPAP values: .13 - .95

Was I happy?

Statistical tests: Were the right ones Statistical tests: Were the right ones used?used?

Demographics: 7 groups: ANOVA used.. not 42 T-Tests

Linear Regression: Not single order correlations. Symbol is r

DV: school attendance: interval data: 1-21 days.

Variables entered into the computer in a step-wise manner based on the TPB:

1st: Demographics then TPB concepts

Theory of Planned BehaviorTheory of Planned Behavior

Demographics TBP Constructs

Intention predicts behavior

Outcome

Age SN

School success PC Intention Behavior

SESGPAFx Hx

Attitude

What are correlations?

The relationship between the IV (x axis) and the DV (the y axis)

R= .6: for every 1 on the Y axis the x axis line goes up .6

What does Regression mean?

All the little dots are each data point (i.e each score)

r refers to how much y (DV) changes in relationship to X (IV)

The solid line is the line of “best fit”

Ven Diagrams and correlations

IV Red (attitude) IV Blue (social norm) DV Yellow

(attendance) Orange: what attitude

contributes uniquely to attendance (beta wt)

R2 = orange + white + green

DV: C = School attendance:

IV: A= Attitude: r = AC + ABC R2= ACbeta = AC IV: B= Social Norm r = BC+ABC beta= BC

Visualizing Shared and Unique variance: How much do we understand about the DV?

Single order correlations can be Single order correlations can be deceiving! deceiving!

IVs beta F p

Attitude .006 .96

Perceived Control

.098 .45

Social Norm

.159 .17

Intention .234 .63

Full Model

3.07 .023

A PC SN ISchool(DV)

.06(.67)

.25(.09)

.29(.04)

.33(.01)

A .10(.52)

.00(.99)

.06(.69)

PC .28(.05)

.38(.00)

SN .22(.10)

Did the theory (model) work? How do Did the theory (model) work? How do you know?you know?

Why are the R2 and Adjusted R2 Why are the R2 and Adjusted R2 different (think sample size!)different (think sample size!)

R2 Adjusted R2 F P(.05)

.140 .093 3.007 .023

Does the TBP help us Does the TBP help us understand school attendance?understand school attendance?IVs: Demographics: Did not predict school attendance:P = .28 - .62

IVs: Attitude + Social Norm + Perceived Control +Intention Predicted DV: School Attendance

Why is this a helpful thing to know?

Confidence Intervals

If crosses 0 or 1 then results are not significant

The larger dot is the mean

The line relates SD: p value (p = .05 then line = .95)

Effect Size: Chi Square

Small Effect size: Don’t smoke: CA Med Effect size: smoke: CA Lge ES: smoke/emphsyema/fx hx

Df N-1 Sm Med LGE

1 795 87 26

2 964 107 39

3 1090 121 44

Effect Size: t test/ANOVA

Small Effect: Med Effect: Lge Effect

Df N-1 Small Med Large

2 393 67 26

3 322 52 21

4 274 45 18

ANOVA: More than 2 groups

Where is the difference?? Post Hoc will tell you! i.e.: Significant difference between

groups 1& 3 and 1 & 4; 3 & 4Group X= Minutes

of exerciseX = Weight loss (lbs)

P value

1 0 -.1 .04

2 30 .2 .02

3 15 .3 .05

4 45 .8 .01

Did they use the right test?

• Why we need p values• Chi Square: comparing two or more

groups using %

Did they use the right tests: means

T test: comparing the means of two groups

ANOVA comparing the means of three or more groups Did they do a post hoc test

Did they do the right tests: comparisons

Correlations: comparing two variables ( 1 IV & 1 DV) on a continuum

Regression: there is more then one IV and there is one DV IV 1 + IV2 + IV3 = DV

P values and fishing expeditions

What does a p value of .05 mean?So… if I do 100 comparisons.. How many will be related by chance alone?

How much confidence should I have in statistics?

Statistics don’t lie.. Liars use statistics

Based on what I know about this subject (people, disease) does this make sense

You can have statistical significance, but not clinical significance, but not the other way around!