Add to ORKGTwo common outcomes of Monte Carlo studies in statistics are bias and Type I error rate. Several versions of bias statistics exist but all employ arbitrary cutoffs for deciding when bias is ignorable or non-ignorable. This article argues Type I error rates should be used when assessing bias
The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is ...
We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulati...
For many multivariate twin models, the numerical Type I error rates are lower than theoretically exp...
To help ensure important patterns of bias and accuracy are detected in Monte Carlo studies in statis...
The familywise Type I error rate is a familiar concept in hypothesis testing, whereas the per‑family...
When conducting a statistical test one of the initial risks that must be considered is a Type I erro...
Can we trust published results? Problems with bias in reported results: “Do social scientists even k...
The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Qu...
The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Qu...
A Monte Carlo simulation study was conducted to examine outliers’ influence on Type I error rates in...
Preliminary tests for homoscedasticity may be unnecessary in general linear models. Based on Monte C...
A common practice in motor behavior research is to analyze Variable Error data with a repeated measu...
Type I errors are a common problem in factorial ANOVA and ANOVA based analyses. Despite decades of l...
Type I error rates in multiple regression, and hence the chance for false positive research findings...
I use Monte Carlo simulations, the jackknife and multiple forms of the bootstrap to study a comprehe...
The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is ...
We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulati...
For many multivariate twin models, the numerical Type I error rates are lower than theoretically exp...
To help ensure important patterns of bias and accuracy are detected in Monte Carlo studies in statis...
The familywise Type I error rate is a familiar concept in hypothesis testing, whereas the per‑family...
When conducting a statistical test one of the initial risks that must be considered is a Type I erro...
Can we trust published results? Problems with bias in reported results: “Do social scientists even k...
The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Qu...
The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Qu...
A Monte Carlo simulation study was conducted to examine outliers’ influence on Type I error rates in...
Preliminary tests for homoscedasticity may be unnecessary in general linear models. Based on Monte C...
A common practice in motor behavior research is to analyze Variable Error data with a repeated measu...
Type I errors are a common problem in factorial ANOVA and ANOVA based analyses. Despite decades of l...
Type I error rates in multiple regression, and hence the chance for false positive research findings...
I use Monte Carlo simulations, the jackknife and multiple forms of the bootstrap to study a comprehe...
The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is ...
We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulati...
For many multivariate twin models, the numerical Type I error rates are lower than theoretically exp...