Book Review: Grit: The Power of Passion and Perseverance

I first stumbled across the research of Angela Duckworth after she was awarded the prestigious MacArthur Fellowship in 2013 for her work investigating the character traits that impact the achievement of long-term goals. So, when it was announced that she would be publishing a book in 2016, I immediately pre-ordered copy so that I could dig into her insights as soon as possible. When I received my copy of Grit: The Power of Passion and Perseverance in the mail, I was excited to crack it open… and then the self-doubt settled in. “What if, after reading the brilliant ideas of a scholar whom I highly regard, I realize that I have no grit… What if I don’t have what it takes?” I was terrified. But, I am convinced that I am not alone. In our current educational culture, one that reinforces a transactional ideology that success is unequivocally defined by test scores and GPA, what is one to do if they literally do not “measure up” to the competition? Is that the end of the road? Is success forever out of reach

Marginal Maximum Likelihood Estimation of Item Response Models in R

Item response theory (IRT) models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.