Entries by Nathan Thompson, PhD

The Standard Error of Measurement

The standard error of measurement is one of the core concepts in psychometrics.  One of the primary assumptions of any assessment is that it is accurately and consistently measuring whatever it is we want to measure.  We therefore need to demonstrate that it is doing so.  There are a number of ways of quantifying this, […]

The Standard Error of the Mean

The standard error of the mean is one of the three main standard errors in psychometrics and psychology.  Its purpose is to help conceptualize the error in estimating the mean of some population based on a sample.  The SEM is a well-known concept from the general field of statistics, used in an untold number of […]

What validity threats are relevant to psychometric forensics?

Validity, in its modern conceptualization, refers to evidence that supports our intended interpretations of test scores (see Chapter 1 of APA/AERA/NCME Standards for full treatment).  Validity threats are issues that issues that hinder the interpretations and use of scores.  The word “interpretation” is key because test scores can be interpreted in different ways, including ways […]

What is classical item difficulty (P value)?

One of the core concepts in psychometrics is item difficulty.  This refers to the probability that examinees will get the item correct for educational/cognitive assessments or respond in the keyed direction with psychological/survey assessments (more on that later).  Difficulty is important for evaluating the characteristics of an item and whether it should continue to be part of […]

Examinee Collusion: Primary vs Secondary

It’s October 30, 2017, and collusion is all over the news today… but I want to talk about a different kind of collusion.  That is, non-independent test taking.  In the field of psychometric forensics, examinee collusion refers to cases where an examinee takes a test with some sort of external help in obtaining the correct […]

Machine Learning in Psychometrics: Old News?

In the past decade, terms like machine learning, artificial intelligence, and data mining are becoming greater buzzwords as computing power, APIs, and the massively increased availability of data enable new technologies like self-driving cars. However, we’ve been using methodologies like machine learning in psychometrics for decades. So much of the hype is just hype. So, what […]