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linear假设等效于R中的ols命令(rms包)

[英]linearHypothesis equivalent for ols command (rms package) in R

I am trying to use "linearHypothesis" function from "car" package to test coefficients of a model estimated with "ols" from "rms" package. 我试图使用“car”包中的“linearHypothesis”函数来测试从“rms”包中用“ols”估计的模型的系数。 The function works with "lrm" objects but not with "ols" objects. 该函数适用于“lrm”对象,但不适用于“ols”对象。 Have you got any alternatives? 你有其他选择吗? I know that using "lm" would sort the issue but I want to use "ols" since it is easier getting clustered standard errors there. 我知道使用“lm”会对问题进行排序,但我想使用“ols”,因为它更容易在那里获得集群标准错误。

You can use glht from the multcomp package. 您可以使用multcomp包中的glht

library(rms)
library(multcomp)

d <- datadist(swiss); options(datadist="d")
fit <- ols(Fertility ~ ., data = swiss)
summary(fit)

test <- glht(fit, linfct = "Agriculture = 0")
summary(test)
# Fit: ols(formula = Fertility ~ ., data = swiss, x = TRUE)
# 
# Linear Hypotheses:
#                  Estimate Std. Error z value Pr(>|z|)  
# Agriculture == 0  -0.1721     0.0703  -2.448   0.0144 *
#   ---
#   Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

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