Exercise 3:    Create table 1 “Characteristics of study population”

·         This exercise will use demo2 project. If you have not started demo2 project, click here to follow exercise 1: start the new project demo2

·         This exercise will use new variables. Click here to follow through Exercise 2:  Create new variables, code and label variables, if you have not done so.

Objective:

To create following table:

Characteristics of study population

Male

Female

P value

N

417

415

AGE

38.4 ± 14.7

37.3 ± 13.1

0.242

HEIGHT

1.6 ± 0.1

1.5 ± 0.1

<0.001

WEIGHT

56.4 ± 7.1

50.4 ± 6.8

<0.001

Body mass index

20.9 ± 2.0

21.5 ± 2.5

0.001

SBP

132.1 ± 22.0

128.5 ± 23.0

0.026

DBP

69.6 ± 11.7

69.3 ± 11.0

0.725

Education

<0.001

Elementary or lower

80 (19.2%)

262 (63.7%)

Middle school

155 (37.3%)

104 (25.3%)

High school or above

181 (43.5%)

45 (10.9%)

Occupation

0.512

Farmer

197 (47.4%)

204 (49.6%)

Others

219 (52.6%)

207 (50.4%)

Cigarette smoking

<0.001

No

119 (28.7%)

377 (92.0%)

Yes

296 (71.3%)

33 ( 8.0%)

Alcohol consumption

<0.001

No

286 (69.6%)

407 (99.3%)

Yes

125 (30.4%)

3 ( 0.7%)

 

Follow following steps to create the above table:

·         Click “Advanced analysis” -> “Population description”

·         Drag and drop variable AGE, HEIGHT, WEIGHT, BMI, SBP, DBP, EDUC, OCCU, SMK, ALH from right panel of variables list to “Select row variables” list (double click the variable name in right panel will do the same).

·         Drag and drop SEX (or select it from drop down list) to “Selected column (stratified) variable”

            

·         Click “View Table” button, wait for a few seconds, you will get the above table

 

Done!

 

Notes:

·         Output table from Empower(R) will have 1 more column of p value, which is nonparametric test for continuous variables and Fisher exact test for categorical variables if it is appropriate.

·         Select column format will change the output format.

·         Column stratified variable (here is SEX) is optional.  Without column variable, no statistical tests will be done (no p value column)