Missing Data Methods for Partial Correlations.

  title={Missing Data Methods for Partial Correlations.},
  author={Gina M. D'Angelo and Jingqin Luo and Chengjie Xiong},
  journal={Journal of biometrics & biostatistics},
  volume={3 8}
In the dementia area it is often of interest to study relationships among regional brain measures; however, it is often necessary to adjust for covariates. Partial correlations are frequently used to correlate two variables while adjusting for other variables. Complete case analysis is typically the analysis of choice for partial correlations with missing data. However, complete case analysis will lead to biased and inefficient results when the data are missing at random. We have extended the… CONTINUE READING

From This Paper

Topics from this paper.

Similar Papers

Loading similar papers…