Stata: Statistical Software for Regulatory Compliance in Clinical Trials
Stata has been widely used for decades in various research domains such as economics, biosciences, health and social sciences, including clinical trials. It is widely referenced in studies published in reputable scientific journals. While SAS has a longer history of being explicitly referenced by regulatory agencies such as the FDA, Stata can still meet regulatory compliance requirements in clinical trials. StataCorp actively engages with researchers, regulatory agencies, and industry…
P Values, Confidence Intervals and Clinical Trials
P values are so ubiquitous in clinical research that it’s easy to take for granted that they are being understood and interpreted correctly. After all, one might say, they are just simple proportions and it’s not brain surgery. At times, however, it's the simplest of things that are easiest to overlook. In fact, the definitions and interpretations of p values are sufficiently subtle that even a minute pivot from…
The role of Biostatisticians, Bioinformaticians & other Data Experts in Clinical Research
As a medical researcher or a small enterprise in the life sciences industry, you are likely to encounter many experts using statistical and computational techniques to study biological, clinical and other health data. These experts can come from a variety of fields such as biostatistics, bioinformatics, biometrics, clinical data science and epidemiology. Although these fields do overlap in certain ways they differ in purpose, focus, and application. All four…
Sex Differences in Clinical Trial Recruiting
The following article investigates several systematic reviews into sex and gender representation in individual clinical trial patient populations. In these studies sex ratios are assessed and evaluated by various factors such as clinical trial phase, disease type under investigation and disease burden in the population. Sex differences in the reporting of safety and efficacy outcomes are also investigated. In many cases safety and efficacy outcomes are pooled, rather than…
Latent Variable Modelling And The Chi Squared Exact Fit Statistic
Latent variable models are statistical tools used extensively throughout clinical and experimental research in medicine and the life sciences. Disciplines such as psychology and neuroscience routinely employ these models to answer complex research questions ranging from the impact of personality traits on workplace success (1) to measuring inter-correlated activity in neural populations based on neuroimaging data (2). Through latent variable modelling, dispositions, states, or processes that must be inferred…