Journal Of Statistics Education Research Articles

Regression-based mediation analysis: a formula for the bias due to an unobserved precursor variable

Researchers want to know whether the change in an explanatory variable X affects the change in a response variable Y (i.e., X causes Y). In practice, there can be two causal paths from X to Y, the path through a mediating variable M (indirect effect) and the path not through M (direct effect). The parameter estimation and hypothesis testing can be performed by a regression-based mediation model. It is already known that randomization of X is not enough for unbiased estimation, and the bias due to an unobserved variable has been discussed in literature but often overlooked. In this article, we first review the challenge under a simple mediation model, then we provide a formula for the exact bias due to an unobserved precursor variable W, the variable which potentially causes the changes in X, M, and/or Y. We present simulation studies to demonstrate the impact of an unobserved precursor variable on hypothesis testing for indirect effect and direct effect. The simulation results show that the inflation of type I error is serious particularly in a large sample study. To numerically demonstrate the formula of the exact bias, a popular data set published in a journal of statistics education is revisited, and we quantify why the conclusion of data analysis can be different before and after accounting for the precursor variable. The result shall remind the importance of a precursor variable in mediation analysis.

Interview With Nicholas J. Horton

AR: Thanks very much, Nick, for agreeing to be interviewed for the Journal of Statistics Education. I’m anxious to hear your thoughts on statistics education in the present, but let’s start a few y...

Interview with Ann Watkins

(2015). Interview with Ann Watkins. Journal of Statistics Education: Vol. 23, No. 2, pp. null.

Teaching Bits: Statistics Education Articles from 2015

(2015). Teaching Bits: Statistics Education Articles from 2015. Journal of Statistics Education: Vol. 23, No. 2, pp. null.

Teaching Bits: What's New with CAUSEweb and MERLOT?

(2013). Teaching Bits: What's New with CAUSEweb and MERLOT? Journal of Statistics Education: Vol. 21, No. 2, pp. null.

Data Representativeness: Issues and Solutions

In its control programmes on maximum residue level compliance and exposure assessments, EFSA requires the participating countries to submit results, from specific numbers of food item samples, analyzed in the countries. These data are used to obtain estimates such as the proportion of samples exceeding the maximum residue limits, and the mean and maximum residue concentration per food item to assess exposure. An important consideration is the design and analysis of the programmes. In this report, we combine elements of survey sampling methodology, and statistical modeling, as a benchmark framework for the programmes, starting from the translation of research questions into statistical problems, to the statistical analysis and interpretation. Particular focus is placed on the issues that could affect the representativeness of the data, and remedial procedures are proposed. For example, in the absence of information on the sampling design, a sensitivity analysis, across a range of designs, is proposed. On the other hand, weighted generalized linear mixed models, and generalized linear mixed models combining both conjugate and normal random effects, are proposed, to address selection bias. Likelihood-based analysis methods are also proposed to address missing and censored data problems. Suggestions for improvements in the design and analysis of the programmes are also identified and discussed. For instance, incorporation of stratified sampling methodology, in determining both the total number, and the allocation of samples to the participating countries, is proposed. All through the report, statistical analysis models which properly take into account the hierarchical (and thus correlated) structure in which the data are collected are proposed.

Teaching Bits: Statistics Education Articles from 2014

(2014). Teaching Bits: Statistics Education Articles from 2014. Journal of Statistics Education: Vol. 22, No. 2, pp. null.

Teaching Bits: Statistics Education Articles from 2014

(2014). Teaching Bits: Statistics Education Articles from 2014. Journal of Statistics Education: Vol. 22, No. 3, pp. null.

Teaching Bits: Statistics Education Articles from 2013 and 2014

(2014). Teaching Bits: Statistics Education Articles from 2013 and 2014. Journal of Statistics Education: Vol. 22, No. 1, pp. null.

Interview with Christine Franklin

(2013). Interview with Christine Franklin. Journal of Statistics Education: Vol. 21, No. 3, pp. null.

Teaching Bits: Statistics Education Articles from 2013

(2013). Teaching Bits: Statistics Education Articles from 2013. Journal of Statistics Education: Vol. 21, No. 2, pp. null.

What Might a Twenty-Year Old Conference Tell us About the Future of Our Profession?

The 1993 inaugural issue of the Journal of Statistics Education (JSE) published an article about a small conference for Principal Investigators (PIs) and co-PIs of twelve projects in statistics education funded by the National Science Foundation (NSF). This twenty-year retrospective (1) offers some personal memories related to the founding of JSE, (2) offers some thoughts about the legacies of the twelve funded projects, (3) sets out a sense of how the conference themes have fared over the last twenty years, and (4) indicates what this might suggest about the future of our profession. In conclusion, I argue (briefly) that at this moment in its history, statistics education faces the biggest opportunity and challenge of its last 40 years.

Interview with David Moore

(2013). Interview with David Moore. Journal of Statistics Education: Vol. 21, No. 2, pp. null.

Teaching Bits: Statistics Education Articles from 2013

(2013). Teaching Bits: Statistics Education Articles from 2013. Journal of Statistics Education: Vol. 21, No. 2, pp. null.

Cooperative Learning Revisited: From an Instructional Method to a Way of Life

(2013). Cooperative Learning Revisited: From an Instructional Method to a Way of Life. Journal of Statistics Education: Vol. 21, No. 2, pp. null.

Celebrating 20 Years of the Journal of Statistics Education

Celebrating 20 Years of the Journal of Statistics Education

Teaching Bits: What's New with CAUSEweb and MERLOT?

(2013). Teaching Bits: What's New with CAUSEweb and MERLOT? Journal of Statistics Education: Vol. 21, No. 2, pp. null.

Teaching Bits: Statistics Education Articles from 2012 and 2013

(2013). Teaching Bits: Statistics Education Articles from 2012 and 2013. Journal of Statistics Education: Vol. 21, No. 1, pp. null.

Department of Research on K-12 Statistics Education

(2013). Department of Research on K-12 Statistics Education. Journal of Statistics Education: Vol. 21, No. 1, pp. null.

Teaching Bits: What's New with CAUSEweb and MERLOT?

(2011). Teaching Bits: What's New with CAUSEweb and MERLOT? Journal of Statistics Education: Vol. 19, No. 3, pp. null.