Nonparametric tests for trendĭo responses have an increasing or decreasing trend? Find out using one of four nonparametric tests for trend: Have excess zeros (or responses in the lowest category)? Incorporate prior knowledge, see posterior distributions of random effects, compute Bayesian predictions, and more. What is the probability of default for a low-risk portfolio?.How likely is it that an extra year of schooling will increase wages?.Bayesian panel-data modelsīayesian analysis lets you answer probabilistic questions with panel-data models. Stata's new xtmlogit command models categorical outcomes that change over time. You can model categorical outcomes with mlogit. Graphically summarize meta-analysis resultsĭetect potential outliers. Extract individual components from datetime values and variables.Īre there influential studies in your data? Use leave-one-out meta-analysis to find out.

Calculate relative dates, or dates from other dates, such as the previous or next birthday or anniversary relative to a reference date.

Calculate durations, such as ages and other differences between datetimes.

Use treatment-effects estimation with lasso variable selection. When you want: Causal inference, average treatment effects, potential-outcome means, double-robust estimationĪnd you have: Many (maybe hundreds or thousands of) potential covariates Now fit your Bayesian VAR models with bayes: var. You fit your Bayesian regression models with bayes. Multivariate meta-analysisĭo you have multiple effect sizes? Do they share a common control group? Do they share the same group of subjects? Multivariate meta-analysis can help. And you don't want to make parametric assumptions. But you don't know the exact event times-only the intervals in which events happen.

Use panel data or repeated cross-sections.

Control for confounding unobserved group and time characteristics.

Evaluate the effect of a policy, a treatment, or an intervention.

Stata output, graphs, and tables seamlessly integrate with your Jupyter Notebook.ĭifference-in-differences (DID) and DDD models.

Access results from Stata analyses within Python.

Easily reproduce your work and collaborate with others.

Invoke Stata and Mata from Jupyter Notebook.

Use Stata from Jupyter Notebook, Spyder, P圜harm IDE, and more.

Exchange data, metadata, and results seamlessly.

Het ontwikkelteam heeft versie 17.0 uitgebracht en hierin zijn de volgende veranderingen en verbeteringen aangebracht: Tables

Voor meer informatie verwijzen we naar deze pagina. Het kan de data beheren, statistische analyses uitvoeren, simuleren en regressies analyseren. Stata is een softwarepakket voor statistiek en wordt veel toegepast in de economie, sociologie en epidemiologie.

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