IC note Calculating and interpreting information criteria icc Intraclass correlation coefficients Inequality Inequality, poverty, and other distributional summaries intreg Interval regression intreg postestimation Postestimation tools for intreg ivfpoisson Fractional probit model with continuous endogenous covariates ...
S458758 REG_SS: Stata module to compute confidence intervals, standard errors, and p-values in a linear regression in which the regressor of interest has a shift-share structure by Rodrigo Adão & Michal Kolesár & Eduardo Morales & Xiang Zhang S458757 SGPV: Stata module to calculate Secon...
To draw inferences based on the regression models you fit, you need to ensure that the methods for estimating standard errors or otherwise calculating confidence intervals and p-values are robust to violations of the i.i.d. assumption. For instance, if you are after an average treatment effect...
PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing 3 PSACALC: Stata module to calculate treatment effects and relative degree of selection under proportional selection of observables and unobservables 4 ESTOUT: Stata ...
S458758 REG_SS: Stata module to compute confidence intervals, standard errors, and p-values in a linear regression in which the regressor of interest has a shift-share structure byRodrigo Adão & Michal Kolesár & Eduardo Morales & Xiang Zhang ...
histogram Histograms for continuous and categorical variables IC note Calculating and interpreting information criteria icc Intraclass correlation coefficients Inequality Inequality, poverty, and other distributional summaries intreg Interval regression intreg postestimation Postestimation tools for intreg ivfpoisson ...
and test_short_name + " " or "" for threshold in thresholds: if pval < threshold[0]: pval_text = "p ≤ {}".format(threshold[1]) break else: pval_text = "p = {}".format(pvalue_format).format(pval) return text + pval_text def validate_arguments(perform_stat_test,...
2.5.2.2. Calculating other confidence intervals 如果我们所设的 CI 不是 95%,而是 99%(p=99%), 那此时的 lower/upper boundary 怎么算呢? Lower boundary: z=\overline{X}-({z} _\frac{1-p} {2} \times SE) Upper boundary: z=\overline{X}+({z} _\frac{1-p} {2} \times SE) p ...
so there are a lot of them. The predictions will be saved in a separate dataset. Once you have the predictions, we provide commands so that you can graph summaries of them and perform hypothesis testing. And you can use them to obtain posterior predictivep-values to check the fit of your...
There is no by() option currently; however, it is rather simple to separate groups and perform a pyears on each to achieve the same result. In fact, doing this yourself allows calculation of numerous person-year strata. The example below provides the results of calculating both individual ...