The standard error of measurement (SEM) 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 […]
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 […]
One of my graduate school mentors once said in class that there are three standard errors that everyone in the assessment or I/O Psych field needs to know: mean, error, and estimate. They are quite distinct in concept and application but easily confused by someone with minimal training. I’ve personally seen the standard error of […]
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 hinder the interpretations and use of scores. The word “interpretation” is key because test scores can be interpreted in different ways, including ways that are […]
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 […]
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 […]
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 […]
An emerging sector in the field of psychometrics is the area devoted to analyzing test data to find cheaters and other illicit or invalid testing behavior. We lack a generally agreed-upon and marketable term for that sort of work, and I’d like to suggest that we use Psychometric Forensics. While research on this topic is more […]
Last week, I had the opportunity to attend the 2017 Conference on Test Security (COTS), hosted by the University of Wisconsin-Madison. If your organization has any concerns about test security (that is, you have any sort of real stakes tied to your test!), I recommend that you attend COTS. It has a great mix of […]
The British statistician George Box is credited with the quote, “All models are wrong but some are useful.” As psychometricians, it is important that we never forget this perspective. We cannot be so haughty as to think that our psychometric models actually represent the true underlying phenomena and any data that does not fit nicely […]
