我计划在R中运行具有随机和/或固定影响的阻塞回归,以检查未观察到的异质性。现在我还没有找到任何关于如何在R中做到这一点的信息,仅是Stata中的一个函数。有人熟悉吗?
这是我的博客堵塞回归示例:
model_simple <- as.formula("completion_yesno ~ ac + ov + UCRate + FirstWeek + LastWeek + DayofWeekSu + DayofWeekMo + DayofWeekTu + DayofWeekWe + DayofWeekTh + DayofWeekFr + MonthofYearJan + MonthofYearFeb + MonthofYearMar + MonthofYearApr +MonthofYearMay+ MonthofYearJun + MonthofYearJul + MonthofYearAug + MonthofYearSep + MonthofYearOct + MonthofYearNov")
clog_simple1 = glm(model_simple,data=cllw,family = binomial(link = cloglog))
summary(clog_simple1)
您可以使用标准的glm
功能拟合固定效果模型。您只需要按兴趣级别创建一个虚拟对象。例如,某种口味的东西:
model_FE <- as.formula("completion_yesno ~ factor(groupvar) + ac + ov + UCRate + FirstWeek + LastWeek + DayofWeekSu + DayofWeekMo + DayofWeekTu + DayofWeekWe + DayofWeekTh + DayofWeekFr + MonthofYearJan + MonthofYearFeb + MonthofYearMar + MonthofYearApr +MonthofYearMay+ MonthofYearJun + MonthofYearJul + MonthofYearAug + MonthofYearSep + MonthofYearOct + MonthofYearNov")
glm(model_simple,data=cllw,family = binomial(link = cloglog))
factor(group)
将创建K-1(或K,如果您想在没有截距的情况下拟合模型)系数。