11.5 Including missing data in demographics tables
“Table 1” in a healthcare study is often a demographics table of an “explanatory variable of interest” against other explanatory variables/confounders.
Do not silently drop missing values in this table.
It is easy to do this correctly with summary_factorlist().
This function provides a useful summary of a dependent variable against explanatory variables.
Despite its name, continuous variables are handled nicely.
na_include=TRUE ensures missing data from the explanatory variables (but not dependent) are included.
To include missing values from the dependent, add na_include_dependent = TRUE.
Including a total column (total_col = TRUE) is also useful, as well as column totals (add_col_totals = TRUE).
If you are using a lot of continuous explanatory variables with missing values, then these can be seen easily using add_row_totals = TRUE.
Note that missing data is not included when p-values are generated.
If you wish missing data to be passed to statistical tests, then include na_to_p = TRUE.
# Explanatory or confounding variables
explanatory <- c("age", "sex.factor",
"nodes",
"smoking_mcar", "smoking_mar")
# Explanatory variable of interest
dependent <- "obstruct.factor" # Bowel obstruction
table1 <- colon_s %>%
summary_factorlist(dependent, explanatory,
na_include=TRUE, na_include_dependent = TRUE,
total_col = TRUE, add_col_totals = TRUE, p=TRUE)| label | levels | No | Yes | (Missing) | Total | p |
|---|---|---|---|---|---|---|
| Total N (%) | 732 (78.8) | 176 (18.9) | 21 (2.3) | 929 | ||
| Age (years) | Mean (SD) | 60.2 (11.5) | 57.3 (13.3) | 63.9 (11.9) | 59.8 (11.9) | 0.004 |
| Sex | Female | 346 (47.3) | 91 (51.7) | 8 (38.1) | 445 (47.9) | 0.330 |
| Male | 386 (52.7) | 85 (48.3) | 13 (61.9) | 484 (52.1) | ||
| nodes | Mean (SD) | 3.7 (3.7) | 3.5 (3.2) | 3.3 (3.1) | 3.7 (3.6) | 0.435 |
| Smoking (MCAR) | Non-smoker | 500 (68.3) | 130 (73.9) | 15 (71.4) | 645 (69.4) | 0.080 |
| Smoker | 154 (21.0) | 26 (14.8) | 3 (14.3) | 183 (19.7) | ||
| (Missing) | 78 (10.7) | 20 (11.4) | 3 (14.3) | 101 (10.9) | ||
| Smoking (MAR) | Non-smoker | 456 (62.3) | 115 (65.3) | 14 (66.7) | 585 (63.0) | 0.822 |
| Smoker | 112 (15.3) | 26 (14.8) | 3 (14.3) | 141 (15.2) | ||
| (Missing) | 164 (22.4) | 35 (19.9) | 4 (19.0) | 203 (21.9) |