Click on the following links. Please note these will open in a new window.

Article 1: Newman, D. A. (2014). Missing data: Five practical guidelines. Organizational Research Methods, 17(4), 372–411.

Description: The author discusses issues related to missing data in research. The author focuses on the types of missing data that exists, what leads to missing data, statistical issues that arise from missing data, and choices that a researcher must make to deal with missing data. The author concludes that social sciences often choose methods that are more prone to bias and error and provides guidelines for better handling of missing data.

Article 2: Culpepper, S. A., & Aguinis, H. (2011). R is for revolution: A cutting-edge, free, open source statistical package. Organizational Research Methods, 14(4), 735–740.

Description: The authors discuss the advantages and disadvantages of R as a statistical package for analyzing data. Advantages include its ability to conduct multiple types of analyses used in the behavioral sciences, cost, continual updates, and ability to create visual graphs. Disadvantages include limited supporting documentation, programming language, and handling missing data. The authors conclude that R is a viable alternative with growing popularity.