Table 2.
Demographics of Our Analysis Sample and Comparison to Participants Who Could Not Be Included in Our Sample.
| Demographic | Those who posted on NRT; our analysis sample (n = 438, 60.83%) | Those who did not post on NRT; thus missing from the analyses (n = 282, 39.17%) | Test statistic comparing the two groups |
|---|---|---|---|
| Age | 39.45 | 39.02 | F = .34, P = .559 |
| Gender (female) | 355/438 (81.05%) | 223/282 (79.08%) | χ2 = .42, P = .516 |
| Ethnicity (non-Hispanic white) | 358/434 (82.49%) | 222/279 (79.57%) | χ2 = .95, P = .329 |
| Marital status (married) | 262/436 (60.09%) | 156/278 (56.12%) | χ2 = 1.11, P = .293 |
| Employment (employed) | 249/436 (57.11%) | 170/278 (61.15%) | χ2 = 1.14, P = .285 |
| Education (some college) | 296/438 (67.58%) | 184/282 (65.25%) | χ2 = .42, P = .517 |
| Cigarettes per day | 17.16 | 17.95 | F = 1.90, P = .168 |
Note. We used chi-square tests to compare the two groups (analysis sample vs missing) on binary scaled demographics, and t-tests to compare them on interval scaled demographics. Additional analyses conducted similarly showed that, among participants who posted on NRT, those who reported their NRT usage (n = 339) did not differ significantly from participants who failed to report NRT usage (n = 99) on age (P = .103), gender (P = .071), ethnicity (P = .579), marital status (P = .321), employment status (P = .230), education level (P = .081), or cigarettes per day (P = .085). All these analyses were bivariate. Percentages in the column heads were calculated based on n/720, referring to all treatment participants.