错误:请提供起始值 [英] Error: please supply starting values
问题描述
fit< -glm(Outcome〜Group,data = data.1,family = binomial(link =log))
,它的工作正常。
我试着把年龄放在模型中,它仍然可以正常工作。
但是,当我将BMI放在模型中时,它给了我以下内容:
错误:没有有效的系数已被发现:请提供起始值
我已经尝试过不同组合的起始值,如:
fit< -glm(Outcome〜Group + Age + BMI,data = data.1,family = binomial(link =log ,start = c(0,0,0,0)
甚至start =(1,4)或start = 4,但仍然给我错误。
它还说:
glm.fit中的错误(x = c(1,1,1, 1,1,1,1,1,1,1,1,1,1,1,:
'start'的长度应等于4,并对应于c的初始系数),group1,age,bmi)
b
$ b
对此的任何帮助将不胜感激!
已编辑:添加可重现的示例。
N = 50
data.1 = data.frame(Outcome = sample(c(0,0,1),N,rep = T),Age = runif(N,8.58),BMI = RNORM(N, 25.6)
Group = rep(c(0,1),length.out = N))
data.1 $ Group< -as.factor(data.1 $ Group)
fit< -glm(Outcome〜Group,data = data.1,family = binomial(link =log))
coefini = coef(glm(Outcome〜Group + Age + BMI,data = data。 1,family = binomial(link =logit))
fit< -glm(Outcome〜Group + Age + BMI,data = data.1,family = binary(link =log coefini)
经过一些尝试和错误,使用 set.seed(123)
:
coefini = coef(glm(Outcome〜 group + Age,data = data.1,family = binomial(link =log))
fit2< -glm(Outcome〜Group + Age + BMI,data = data.1,family = binary =log),start = c(coefini,0))
摘要(fit2)
调用:
glm(formula = Outcome〜Group + Age + BMI,family = binomial(link =log),
data = data.1,start = c(coefini,0))
偏差余数:
最小1Q中位数3Q最高
-1.2457 -0.9699 -0.7725 1 .2737 1.6799
系数:
估计标准错误z值Pr(> | z |)
(截取)-1.5816964 1.0616813 -1.490 0.136
Group1 0.4987848 0.3958399 1.260 0.208
年龄0.0091428 0.0138985 0.658 0.511
BMI -0.0005498 0.0331120 -0.017 0.987
(二项式族的分散参数取为1)
空值:65.342在49自由度
剩余偏差:63.456在46度的自由
AIC:71.456
费舍尔计分迭代次数:3
I am conducting a log binomial regression in R. I want to control for covariates in the model (age and BMI- both continuous variables) whereas the dependent variable is Outcome(Yes or No) and independent variable is Group (1 or 2).
fit<-glm(Outcome~Group, data=data.1, family=binomial(link="log"))
and it works fine.
When I try putting age in the model, it still works fine. However, when I put BMI in the model, it gives me the following:
Error: no valid set of coefficients has been found: please supply starting values
I have been tried different combination of starting values such as:
fit<-glm(Outcome~Group+Age+BMI, data=data.1, family=binomial(link="log"), start=c(0,0,0,0)
or even start=(1,4) or start =4 but it still gives me the error.
It also says:
Error in glm.fit(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, :
length of 'start' should equal 4 and correspond to initial coefs for c("(Intercept)", "group1", "age", "bmi")
.
Any help on this will be much appreciated!
Edited: adding reproducible example.
N=50
data.1=data.frame(Outcome=sample(c(0,0,1),N, rep=T),Age=runif(N,8,58),BMI=rnorm(N,25,6),
Group=rep(c(0,1),length.out=N))
data.1$Group<-as.factor(data.1$Group)
fit<-glm(Outcome~Group, data=data.1, family=binomial(link="log"))
coefini=coef(glm(Outcome~Group+Age+BMI, data=data.1,family =binomial(link = "logit") ))
fit<-glm(Outcome~Group+Age+BMI, data=data.1, family=binomial(link="log"),start=coefini)
After some trial and error, using set.seed(123)
:
coefini=coef(glm(Outcome~Group+Age, data=data.1,family =binomial(link = "log") ))
fit2<-glm(Outcome~Group+Age+BMI, data=data.1, family=binomial(link="log"),start=c(coefini,0))
summary(fit2)
Call:
glm(formula = Outcome ~ Group + Age + BMI, family = binomial(link = "log"),
data = data.1, start = c(coefini, 0))
Deviance Residuals:
Min 1Q Median 3Q Max
-1.2457 -0.9699 -0.7725 1.2737 1.6799
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.5816964 1.0616813 -1.490 0.136
Group1 0.4987848 0.3958399 1.260 0.208
Age 0.0091428 0.0138985 0.658 0.511
BMI -0.0005498 0.0331120 -0.017 0.987
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 65.342 on 49 degrees of freedom
Residual deviance: 63.456 on 46 degrees of freedom
AIC: 71.456
Number of Fisher Scoring iterations: 3
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