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

Summary: The author discusses issues related to missing data in research. The author focuses on the types of missing data that exist, 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.

Learning Objectives: Missing Data: Points of View and Choices

Questions to Consider

1. What is missing data? What are the reasons that a data file can have missing data?
2. What are the differences between missing completely at random, missing at random, and missing not at random?
3. What guidelines should a researcher consider when deciding how to handle 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.

Summary: 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.

Learning Objectives: Other Statistical Software

Questions to Consider

1. What is R? How does it compare to SPSS?
2. What advantages does R offer over SPSS? What disadvantages does R have compared to SPSS?
3. How do you think the cost of statistical software impacts the choices individuals and universities make in the future? Should faculty and students be involved in these decisions?
    

Article 3: Starbuck, W. H. (2016). 60^th anniversary essay: How journals could improve research practices in social science. Administrative Science Quarterly, 61(2), 165-183.

Summary: The author discusses ways to improve the evaluation of manuscripts for publication. Special attention is given to problems in the prevalent methodology including HARKing and p-hacking. The author provides guidelines for improving editorial decisions in this context.

Learning Objectives: Opportunistic Biases and “going fishing”

Questions to Consider

1. What is HARKing? What is p-hacking?
2. Why are HARKing and p-hacking a problem for editorial decisions of journals? Why is it a problem for science in general?
3. What suggestions does the author make for making editorial decisions that prevent problems of HARKing and p-hacking? What other suggestions would you make?