# STATS Chapter 14 Assignment

August 30, 2017

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Chapter 14 Assignment Name

Key

SOURCE: Hosmer, D.W., Lemeshow, S. and Sturdivant, R.X. (2013) Applied Logistic Regression: Third Edition. These data are copyrighted by John Wiley & Sons Inc. and must be acknowledged and used accordingly. Data were collected at Baystate Medical Center, Springfield, Massachusetts during 1986.

Description of the Data:The goal of this study was to identify risk factors associated with giving birth to a low birth weight baby (weighing less than 2500 grams). Data were collected on 189 women, 59 of which had low birth weight babies and 130 of which had normal birth weight babies. Four variables which were thought to be of importance were age, weight of the subject at her last menstrual period, race, and the number of physician visits during the first trimester of pregnancy. (See the Excel File “Chapter 14 Dataset” to complete the questions below.)

Variable Names:

ID: Identification Code
LOW: Low Birth Weight (0 = Birth Weight >= 2500g, 1 = Birth Weight < 2500g)
AGE: Age of the Mother in Years
LWT: Weight in Pounds at the Last Menstrual Period
RACE: Race (1 = White, 2 = Black, 3 = Other)
SMOKE: Smoking Status During Pregnancy (1 = Yes, 0 = No)
PTL: History of Premature Labor (0 = None 1 = One, etc.)
HT: History of Hypertension (1 = Yes, 0 = No)
UI: Presence of Uterine Irritability (1 = Yes, 0 = No)
FTV: Number of Physician Visits During the First Trimester (0 = None, 1 = One, 2 = Two, etc.)
BWT: Birth Weight in Grams

Research Question: Is there a relationship between low birth weight (LOW) and smoking status during pregnancy (SMOKE)?

1. What type of test will we perform?

2. Create a contingency table of the data. To do this, you’ll have to count the number of subjects who meet each of the desired criteria (i.e. LOW = 0 and SMOKE = 0, LOW = 0 and SMOKE = 1, etc.) [*Hint: Try using the COUNTIFS function in Excel for easier counting.)

LOW = 0

LOW = 1

Total

SMOKE = 0

SMOKE = 1

Total

189

3. List the assumptions for this type of analysis.

4. Identify the null and alternative hypothesis.

Now, let’s perform our analysis.

In the Excel file, click on Sheet 1 at the bottom of the screen. Insert your values from question 2 into the table. You’ll notice the chi square test statistic, critical value, p-value, and effect sizes are calculated for you. (You’re welcomeDescription: c:\users\jennifer\appdata\local\microsoft\windows\temporary internet files\content.)

5. According to the analysis, what is the expected number of babies with low birth weight born to mothers who smoked during pregnancy? How does this value compare to the observed frequency?

6. Identify the Chi-square test statistic and p-value for testing the claim that there is no association between smoking and low birth weight. Calculate the degrees of freedom and input this value into Excel.

Test statistic:

p-value:

Degrees of freedom:

7. Identify the effect size. What type of association is indicated by the effect size?

Calculate the odds ratio of a mother who smokes during pregnancy giving birth to a low birth weight baby compared to a mother who does not smoke. Input this value into the Excel file to see the confidence interval of the ratio.

8. What is your calculated odds ratio?

Odds Ratio:

9. How would you interpret the odds ratio?

10. Use APA style reporting to write up your results of this analysis.

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