Sentence examples for missing data testing from inspiring English sources

Chapter 12: Multiple Regression Regression revisited Introducing a second predictor A detailed example Issues concerning normality Missing data Testing for linearity and homoscedasticity A multiple regression: The first pass Addressing multicollinearity Interactions What can go wrong?

Scrutiny included range value testing, missing data testing, logical tests on data consistency across fields, and multiple comparisons with the original paper CRF record.

The last observation carried forward method was used for imputing missing data; testing was two-sided at a significance level of 0.05.

For variables with >10% missing data, tests of interaction were performed when appropriate.

Missing data on testing history and a large proportion of tests analyzed with less sensitive technology will tend to bias the results towards the null because of misclassification of infection status.

Differences between patients with and without missing data were tested using the χ test or Wilcoxon rank-sum test.

After checking for missing data and testing for normality, group differences will be analysed using the Pearson Chi-square test, or likelihood ratio in the case of dichotomous outcomes.

A recent study on missing data at testing stage can be found in [2] where Saar-Tsechansky and Provost evaluate different methods to handle missing data at testing stage.

30 31 We tested whether baseline variables (study, group allocation, age, sex, and baseline depression) predicted missing data to test the assumptions underlying imputation.

When these variables were compared by sex and origin of the participants, we found no differences between complete data and missing data (MCAR test, p = 0.2).

To handle missing data, we tested five methods, including rolling back to a simpler model, excluding incomplete cases, EM algorithm, MI, and median imputation (see Materials and Methods).