(2009). 'Robust regression in Stata', Stata Journal, Vol. 9(3), 439-453.Verardi and Croux (2009). "Robust Regression in Stata". The Stata Journal 9(3), pp. 439- 453.Verardi V, Croux C. Robust regression in Stata. Stata J 2009;9:439-453....
Estimates adjusted for mass points in the running variable. Covariate-adjusted Sharp RD estimates using local polynomial regression. Cutoff c = 0 | Left of c Right of c Number of obs = 704 ---+--- BW type = Manual Number of obs | 400 304 Kernel = Triangular Eff. Number of obs | 1...
...10...20... done (27) Upper bound: ...10...20... done (25) Wild cluster bootstrap Number of obs = 18,925 Linear regression Number of clusters = 12 Cluster size: Cluster variable: ind_code min = 37 Error weight: Rademacher avg = 1577.1 max = 6296 ln_wageEstimate t p-value...
本人农学专业,写论文的时候主编要求做robust nonlinear regression,有因变量(y)和一个自变量(x),两者为指数关系(y=a*exp(b*x)),但是存在我不确定的outliers,我也不好直接按异常值排除,想对它做稳健回归,减小outliers的影响,做完依然是指数形式,但是不知道在stata中怎么实现? 本人这方面白纸一张,请数学大神帮忙看...
p(pvalue) specifies the order of the local polynomial used to construct the point estimator. The default is p(1) (local linear regression).p(pvalue)设定多项式阶数,默认为1,局部线性回归。 kernel(kernelfn) specifies the kernel function used to construct the global polynomial estimators. kernelfn...
AuthorWilliam Sribney, StataCorp Question: I ran a regression with data for clients clustered by therapist. I first estimated the regression without using thevce(clusterclustvar)option, then I re-ran it using thevce(clusterclustvar)option. In many cases, the standard errors were much smaller ...
内容提示: Friday June 9 10:37:09 2017 Page 1®Statistics/Data Analysis{smcl} Title rdrobust Local Polynomial Regression Discontinuity Estimation with Robust Bias−Corrected Confidence Intervals and Inference Procedures.Syntax rdrobust depvar runvar [if] [in] [, c(#) fuzzy(fuzzyvar [sharpbw]...
1. Calculate Robust Standard Errors in STATA In STATA you can obtain robust standard errors simply by adding robust to your regression command. For instance reg dependent_var independent_var, robust 2. Calculate Robust Standard Errors in R It is also possible to estimate robust standard errors in...
Diff-in-Diff | 2.914 | 1.737 | 1.68 | 0.094* --- R-square: 0.01 * Means and Standard Errors are estimated by linear regression **Robust Std. Errors **Inference: *** p<0.01; ** p<0.05; * p<0.1 *---result.over--- 3、
AuthorBill Sribney, StataCorp I once overheard a famous statistician say the robust variance estimator for (unclustered) logistic regression is stupid. His reason was that if the outcome variable is binary then it’s got to be a Bernoulli distribution. It’s not like linear regression with dat...