The same problem occurs if I use an alternative method of prediction: gllapred newvar, xb I have checked to see that I have the same variables in my dataset as in the estimated model. Variable names are in the correct case. The internal order of the variables in my second dataset is ...
I could not find empirical results on out-of-sample results. My question is: Can anybody cite me some sources that deal with out-of-sample prediction comparison based on OLS and GMM estimator? Thanks in advance Niko * * For searches and help try: * http://www.stata.com/support/faqs/...
MMQREG: Stata module to estimate quantile regressions via Method of Moments 17 XTCOINTREG: Stata module for panel data generalization of cointegration regression using fully modified ordinary least squares, dynamic ordinary least squares, and canonical correlation regression methods 18 RTMCI: Stata module...
Performance of the DELFIA Express sFlt-1/PlGF ratio <50 to rule-out pre-eclampsia within seven days was comparable to the PROGNOSIS study (Prediction of Short-Term Outcome in Pregnant Women with Suspected Preeclampsia Study), a prospective, multicentre, observational study of performance of assays ...
An automated clinical prediction model for out of intensive care unit (ICU) cardiopulmonary arrest and unexpected death was created in the derivation sample (50% randomly selected from total cohort) using multivariable logistic regression. The automated model was then validated in the remaining 50% ...
Sensitivity and specificity, with 95% confidence interval (CI), were calculated for each set of 2 × 2 data. The bivariate/hierarchical summary receiver operating characteristic (HSROC) model was used to estimate summary sensitivity and specificity with 95% CI and prediction regions around the...
directed acyclic graph of the assumptions underpinning the analytical model: the aim of covariate adjustment was to minimise confounding influences on the association between air pollution exposure and cognitive performance, rather than to construct a multivariable risk prediction model for cognitive outcome...
Ferritin had the best area under the curve (AUC), both for gastrointestinal cancer (0.746, CI: 0.691-0.794), and colorectal cancer (0.765, CI: 0.713-0.813), compared to the other parameters of iron deficiency. In the diagnosis of colorectal cancer, ferritin with ...
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Studies which reported the diagnostic performance of a risk prediction score that included FIT, in addition to measure of the accuracy of FIT alone, were additionally assessed using the prediction study risk of bias assessment tool (PROBAST) [22]. Quality assessment was undertaken by one reviewer ...