clindata_miss {missCompare}

Clinical dataset with missingness

Description

clindata_miss is a custom made dataframe that resembles a real-life clinical dataset. The correlations between variables, the data means, SDs and ranges are realistic, but the dataset is constructed by simulations and manual data input. The dataset contains missing values (approximately 10% missing overall), and values are missing in a realistic pattern.

Usage

clindata_miss

Format

A data frame with 2500 rows and 12 variables:

age

numeric, age, in years, 2.88% missing - in general, age is not likely have lots of missing data in a realistic dataset, therefore only a few values are missing here randomly, e.g. due to mistakes in data input

sex

factor, male=1 and female=2, 2.88% missing - similar to age, sex information is also not likely have missing data in a realistic dataset, no values are missing here

waist

numeric, waist circumference, in cm, 4.12% missing - anthropometric data is easy to collect, therefore only a small fraction is missing here, often missing together with BMI, the other anthropometric variable

BMI

numeric, body mass index, in kg/m2, 4.16% missing - anthropometric data is easy to collect, therefore only a small fraction is missing here, often missing together with waist, the other anthropometric variable

SBP

numeric, systolic blood pressure, in mmHg, 8.84% missing - in a realistic fashion, SBP is almost always missing together with DBP

DBP

numeric, diastolic blood pressure, in mmHg, 8.84% missing - in a realistic fashion, DBP is almost always missing together with SBP

FG

numeric, blood fasting glucose concentration, in mmol/dl, 5.84% missing - often missing together with other clinical variables

PPG

numeric, blood postprandial glucose concentration, in mmol/dl, 53.2% missing - in this simulated dataset, only less than half of the participants had postprandial glucose measurements

TC

numeric, blood total cholesterol concentration, in mmol/dl, 7.2% missing - often missing together with other lipids, TG and HDL-C

TG

numeric, blood triglycerides concentration, in mmol/dl, 7.48% missing - often missing together with other lipids, TC and HDL-C, due to the sensitivity of a hypothetical machine, values below 0.6 are set to -9, upon conversion from -9s to NAs, the missingness fraction is 10.6%

HDL

numeric, blood high density lipoprotein cholesterol concentration, in mmol/dl, 10.76% missing - often missing together with other lipids, TG and TC, due to the sensitivity of a hypothetical machine, values below 0.05 are set to -9, upon conversion from -9s to NAs, the missingness fraction is 13.72%

education

factor, primary school=1, secondary school=2, bsc degree=3, msc degree=4, phd degree=5, 7.16% missing - self reported education missing in a not random fashion, those with lower education are less likely to report their education status

Source

The dataset is simulated and undergone manual configuration.