技術標籤：logistic迴歸 簡介r語言 線性迴歸 相關係數r語言 計算模型的rmser語言logistic迴歸r語言迴歸分析

微訊號：moooshaaa

簡介

The tobit model, also called a censored regression model, is designed to estimate linear relationships between variables when there is either left- or right-censoring in the dependent variable (also known as censoring from below and above, respectively). Censoring from above takes place when cases with a value at or above some threshold, all take on the value of that threshold, so that the true value might be equal to the threshold, but it might also be higher. In the case of censoring from below, values those that fall at or below some threshold are censored.

Syntax

√輸入1：

install.packages("rio")
library(rio)
tbimport("tb.sav")
head(tb)

√結果1：

nonationeducationreligionmarriagesurgicaladmissionabilitywatcherpainscoreSpiritualityfatigueanxietydepression
1123021323228276050
221302021200253154
33130211110076165
441302031518204356
551202111131193965
661202111231183068
 

√輸入2：

install.packages("ggplot2")
library(ggplot2)
ggplot(fqp,aes(x=Spirituality))+geom_histogram(binwidth=1,color="black",fill="lightblue")+theme_classic()

√結果2：

√輸入3：

table(tb$Spirituality)

√結果3：

01234567891011121314151617181920212223252627282930
83404645442719312518151910131249105251111242111
 

√輸入4：

tb[,c(2:8)]2:8)],as.factor)
install.packages("AER")
library(AER)
tobleft=0,right=30,data=tb)
summary(tob)

√結果4：

Call:
tobit(formula=Spirituality~nation+education+religion+
marriage+surgical+admission+ability+watcher+painscore+
fatigue+anxiety+depression,left=0,right=30,data=tb)

Observations:
TotalLeft-censoredUncensoredRight-censored
5068341211

Coefficients:
EstimateStd.ErrorzvaluePr(>|z|)
(Intercept)-4.81734623.4142289-1.4110.158256
nation27.75357582.80505812.7640.005707**
education20.33421791.28229240.2610.794369
education31.26029361.25314261.0060.314557
education41.20966511.37714780.8780.379735
education50.52449391.43148400.3660.714068
religion12.11906510.99783432.1240.033698*
marriage2-6.20443151.9804453-3.1330.001731**
marriage3-5.52687132.6140756-2.1140.034492*
marriage4-4.41667873.0722339-1.4380.150544
surgical12.31730490.65376173.5450.000393***
admission2-0.30997290.9072388-0.3420.732602
admission31.76189131.08557881.6230.104590
admission41.02498640.91556941.1200.262924
ability21.46378590.79933521.8310.067063.
ability33.38000144.07950920.8290.407370
watcher-0.02612210.2562860-0.1020.918816
painscore0.37988340.19368081.9610.049834*
fatigue0.30417300.05169555.8844.01e-09***
anxiety0.14055800.03689993.8090.000139***
depression0.00023810.03546310.0070.994644
Log(scale)1.90885050.036152352.8002e-16***
---
Signif.codes:0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘’1

Scale:6.745

Gaussiandistribution
NumberofNewton-RaphsonIterations:4
Log-likelihood:-1461on22Df
Wald-statistic:195.5on20Df,p-value:2.22e-16

此外，VGAM 和Zelig package 也可以實現Tobit迴歸

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