Sentence examples for missing value analyses from inspiring English sources

The missing value analyses and their imputations were conducted in R (V.3.0.2 for Microsoft Windows) using the MICE package.

Imputation was done using the linear regression method (missing value analyses) available in SPSS for Windows version 13.0 software.

We undertook missing value analyses using logistic regression separately, for each measure of empathy, to examine non-response bias.

Pearson's correlation coefficients and missing value analyses were conducted using Prediction and Analysis Software version 18 (IBM, Somers, NY).

In order to assess the presence of non-response bias, we undertook missing value analyses using logistic regression separately for men and women, for each measure of empathy.

Missing value analyses showed four categorical variables with over 10% missing cases and a category designated as "unknown" was added for those variables.

Missing values analyses revealed that persons with missing values on mental and/or physical function scales were significantly more likely to be lower educated, have fewer basic and luxury goods and have worse physical and mental function scores at the 2004 baseline.

Because parental education was a family-level moderator (i.e., observations within families cannot be considered independent), and because FSIQ scores of subjects from the same family can also not be considered independent, we also performed missing values analyses for the first subjects of each family only.

Ultimately, we created five complete data sets with a different imputed value for each missing value, performed regression analyses separately on each data set, and combined the results to produce confidence intervals that reflected the uncertainty created by the missing values.

A detailed statistical analysis plan (SAP) will be defined in advance to the final analysis, to fix detailed statistical considerations with regard to further data analyses, multiple test issue, missing value imputation and sensitivity analyses.

To compensate for missing values, sensitivity analyses for different assumptions were conducted by repeating the final prediction models.