Grading Computational Public Health Statistics Final Exam / S00

PART A IS WORTH 22 POINTS

1. Confounding is [bias] in a measure of association due to the influence of [extraneous factor(s)].

2. Statistical interaction is the [unanticipated effect] of the [interdependent operation of two or more factors.]

3. Bias is a [systemic] [error in inference].

4. Alpha is either the [probability] the researcher is willing to take in [not capturing a parameter] or the [probability] of making a [type I error / false retention of the null hypothesis]

5. Three forms of bias: [Information bias], [Selection bias], [Confounding]

6. Cohort studies sample [exposed and unexposed groups] and [follow them forward to compare their incidences of disease]. Case-control studies [sample cases and controls] and ["follow them backwards to compare their exposure proportions or odds.]

7. odds ratio

8. Experimental studies entail an [intervention] [on the part of the researcher]. (The intervention is randomly allocated in a randomized controlled clinical trial.)

9. To control the [family-wise] [type I error-rate].

10. Preconditions for confounding:[E & C associated] & [C independent risk factor for D]

Part B

EXF-S00.REC: Death rates associated with exposure (cohort study)

1. One sample problem

p^ = 37 / 99 = 37.4% [2]

95% confidence interval for p: (27.9%, 47.7%) [1]

H0: p = 25% [1]

H1: p not = 25% [1]

Let alpha = .05

Exact binomial test

Two-tailed p value = .0072 (calculated by EpiTable) [1]

Reject H0 [1]

The difference is significantly higher than expected. [1]

2. Relative risk analysis

p^1 = 21 / 47 = 44.7% [1]

p^2 = 16 / 52 = 30.8% [1]

RR^ = 1.45 [1]

95% confidence interval: (0.87, 2.44) [1]

H0: RR = 1 [1]

H1: RR not = 1 [1]

Let alpha = .05

APHA style optional: Chi-squareYates (1, N = 99) = 1.49, p= .22

Chi-square, Yates = 1.49 [1]

df = 1 [1]

p value = .22 [1]

Retain H0 [1]

3. Interaction analysis

RR^1 = 1.21 [1]

RR^2 = 1.90 [1]

H0: RR1 = RR2 [1]

H1: RR1 not = RR2 [1]

Let alpha = .05

Chi-squareInteraction (1, N = 97) = 0.23, p = .63 [3]

Retain H0 [1]

No significant evidence of interaction [1]

4. Confounder analysis

cRR^ = 1.46 (NS) [1]

aRR^ = 1.27 (NS) [2]

These are similar. I would therefore conclude that the potential for interaction is small. [2]

5. BREASTCA: Breast cancer and nulliparity (case-control data).

Two-by-two table [1]

Cases Controls

E+ 250 200 450

E- 150 200 350

400 400 800

Proportion of exposure among cases = 62.50% [1]

Proportion of exposure among controls = 50.0% [1]

OR^ = 1.67 [1]

95% confidence interval for OR: 1.26, 2.21 [1]

H0: OR = 1 [1]

H1: OR not = 1

Let alpha = .05

Chi-square, Yates = 12.20 [1]

df = 1 [1]

p value = .000479 [1]

Reject H0 [1]

Nulliparious have a significant increase in risk. []

Risk estimate - 1.67 times that of women who had children [1]

6. TRIAL: Three Group Clinical Trial

QES file[3]

REC file [2]

Group 1: mean = 3.0, sd = 0.7 n = 5 [1]

Group 2: mean = 6.8, sd = 1.3, n = 5 [1]

Group 3: mean = 7.0, sd = 1.9, n = 5 [1]

Bartlett's

H0: sigma-squared1 = sigma-squared2 = sigma-squared3 [1]

H1: at least one population variance differs [1]

Let alpha = .05

Bartlett's Chi-squared(2, N = 15) = 3.01, p = .22. [1]

Conclusion: retain H0. [1]

ANOVA

H0: 1 = 2 = 3 [1]

H1: at least one population mean differs[1]

Let alpha = .05

F(2,12) = 13.37 [1]

p = .0012 [1]
Reject H0 [1]

Significant difference between group means. [1]

Group 1 much lower than the other two groups. [1]