<p>We simulate 1,000 meta-analysis of 10 studies with varying sample sizes where only a subset of the studies have an effect. Given 10,000 studies, we threshold each statistic to predict the studies having an effect and the studies not having an effect, and vary the threshold to draw the ROC curves. In A, true prediction rate is the proportion of the studies actually having an effect that are correctly predicted to have an effect and false prediction rate is the proportion of the studies actually not having an effect that are incorrectly predicted to have an effect. In B, true and false prediction rates are similarly defined but in the direction of predicting studies not having an effect. For BF, we use the asymptotic BF of Wakefield <a hre...
<p>ROC curves are plotted at different TM-score cut-offs. TPR – true positive rate, FPR – false posi...
<p>A total of <i>m</i> null hypotheses are tested. FP is the number of Type I errors or the number o...
<p>Performance is measured by Relative Predictive Gain (RPG). True PVE = 0.6. Means and standard dev...
Evaluating the performance of models predicting a binary outcome can be done using a variety of meas...
<p>Here, a propensity score was calculated as the relative propensity of a pattern between the backg...
<p>Subfigure A: The ROC curves for three data sources (“Chem”: chemical structure, “Inter”: target p...
<p>Reproducibility () vs prediction accuracy curves for two subjects: C Subject S4 (without motor ne...
<p>Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
We develop an inference framework for the difference in errors between 2 prediction procedures. The ...
These results are similar to those presented in Fig 2, except that the decision to publish takes the...
<p>Exp1: Expected value from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
If individual participant data are available from multiple studies or clusters, then a prediction mo...
<p>The null hypothesis is that the AUC ROC values between two methods are the same. Given p-values a...
<p>ROC curves are plotted at different TM-score cut-offs. TPR – true positive rate, FPR – false posi...
<p>A total of <i>m</i> null hypotheses are tested. FP is the number of Type I errors or the number o...
<p>Performance is measured by Relative Predictive Gain (RPG). True PVE = 0.6. Means and standard dev...
Evaluating the performance of models predicting a binary outcome can be done using a variety of meas...
<p>Here, a propensity score was calculated as the relative propensity of a pattern between the backg...
<p>Subfigure A: The ROC curves for three data sources (“Chem”: chemical structure, “Inter”: target p...
<p>Reproducibility () vs prediction accuracy curves for two subjects: C Subject S4 (without motor ne...
<p>Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
We develop an inference framework for the difference in errors between 2 prediction procedures. The ...
These results are similar to those presented in Fig 2, except that the decision to publish takes the...
<p>Exp1: Expected value from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
If individual participant data are available from multiple studies or clusters, then a prediction mo...
<p>The null hypothesis is that the AUC ROC values between two methods are the same. Given p-values a...
<p>ROC curves are plotted at different TM-score cut-offs. TPR – true positive rate, FPR – false posi...
<p>A total of <i>m</i> null hypotheses are tested. FP is the number of Type I errors or the number o...
<p>Performance is measured by Relative Predictive Gain (RPG). True PVE = 0.6. Means and standard dev...