Sample-size analysis for confidence intervals in Stata 16
The new ciwidth command performs Precision and Sample Size (PrSS) analysis, which is sample-size analysis for confidence intervals (CIs). This method is used when you are planning a study and you want to optimally allocate resources when CIs are to be used for inference. Said differently, you use this method when you want to estimate the sample size required to achieve the desired precision of a CI in a planned study.
ciwidth produces sample sizes, precision, and more that are required for the
• CI for one mean
• CI for one variance
• CI for two independent means
• CI for two paired means
The control panel interface lets you select the analysis type and input assumptions to obtain desired results.
ciwidth allows results to be displayed in customizable tables and graphs.
ciwidth also provides facilities for you to add your own methods.
Nonparametric series regression
Stata 16's new npregress series command fits nonparametric series regressions that approximate the mean of the dependent variable using polynomials, B-splines, or splines of the covariates. This means that you do not need to specify any predetermined functional form. You specify only which covariates you wish to include in your model. For instance, type
. npregress series wineoutput rainfall temperature i.irrigation
Instead of reporting coefficients, npregress series reports effects, meaning average marginal effects for continuous variables and contrasts for categorical variables. The results might be that the average marginal effect of rainfall is 1 and the contrast for irrigation is 2. This contrast can be interpreted as the average treatment effect of irrigation.
Being a nonparametric regression, the unknown mean is approximated by a series function of the covariates. And yet we can still obtain the inferences that we could from a parametric model. We just use margins. We could type
. margins irrigation, at(temperature=(40(5)90))
and obtain a table of the expected effect of having irrigation at temperatures of 40, 50, ..., 90 degrees. And we could graph the result using marginsplot.
Even more, npregress series can fit partially parametric (semiparametric) models.
Stata是一款完整的、集成的统计软件包，提供您需要的一切数据分析、数据管理和图形。
快速,简单并易于使用
点击式的界面和强大,直观的命令语言让Stata使用起来快速,精确并易于使用。
所有的分析结果都可以被复制和存档，并用来出版和审查。不管您什么时候写的内容，版本控制系统确保统计程序可继续生成同样的结果。
统计功能介绍
Stata使得大量的统计工具用于指尖
标准方法，如
基本表格和总结
案例对照分析
ARIMA
ANOVA 和MANOVA
线性回归
时间序列平滑
广义线性模型（GLM）
聚类分析
对比和比较
功率分析
样本选择
……
高级方法，如
当Stata执行您的分析或理解使用的方法时，Stata不会让您孤立无援或订购很多书籍来了解每个细节。
我们每一个数据管理功能都有完整的解释，并记录在案，并在实践中显示实际的例子。每一个估计都有完全记录，包含几个真实数据的例子，真正讨论如何解释结果。这些例子都给了数据，您可以直接在Stata中使用，甚至扩展您的分析。我们给您快速启动每一个功能，展示一些较常用用途。想要了解更多细节，我们的方法和公式部分提供了计算的细节，我们参考部分会给出更多信息。
Stata是一个很大的软件包，包含了非常多的文档，**过27卷14,000页的内容。不用担心，在Help菜单中输入要搜索的内容，Stata会搜索到关键词、指数，甚至用户编写的程序包，这些会让您得到想要了解的一切。Stata包含了所有这些您想要的内容。
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