R 和 SPSS 为对数线性分析返回不同的参数

Question

我运行在 R 中对以下研究生招生数据进行对数线性分析。

grad_admissions <- array(data = c(39, 10, 20, 15, 11, 41, 6, 60), 
                         dim = c(2,2,2), 
                         dimnames = list("department" = c("one","two"),
                                         "gender" = c("male","female"),
                                         "admission" = c("admitted","notadmitted")))

ftable(grad_admissions, row.vars = c("department"),col.vars = c("admission","gender"))

grad_admissions.df <- as.data.frame(as.table(grad_admissions))

grad_admissions.df$gender <- factor(grad_admissions.df$gender, levels = c("female","male"))
grad_admissions.df$department <- factor(grad_admissions.df$department, levels = c("two","one"))
grad_admissions.df$admission <- factor(grad_admissions.df$admission, levels = c("admitted","notadmitted"))


mod1 <- glm(Freq ~ department * gender * admission, 
            data = grad_admissions.df, family = poisson)

summary(mod1)

我还在同一数据集（SAV 文件 here）上运行使用以下 SPSS 语法。

DATASET ACTIVATE DataSet2.
WEIGHT BY Count.

GENLOG Gender Admitted Department
  /MODEL=POISSON
  /PRINT=FREQ RESID ADJRESID ZRESID DEV ESTIM CORR COV
  /PLOT=NONE
  /CRITERIA=CIN(95) ITERATE(20) CONVERGE(0.001) DELTA(.5).

参数估计值如下。它们相似但不完全相同。在 SPSS 输出中，男性编码为 0，女性编码为 1。

谁能解释为什么它们不一样？

Answer 1

尝试以下操作：

GENLOG Department Gender Admitted
  /MODEL=POISSON
  /PRINT=FREQ RESID ADJRESID ZRESID DEV ESTIM CORR COV
  /PLOT=NONE
  /CRITERIA=CIN(95) ITERATE(20) CONVERGE(0.001) DELTA(0).

注意 CRITERIA 子命令的 DELTA(0) 规范。默认情况下，SPSS GENLOG 将饱和模型中每个细胞的细胞计数增加 0.5，这是处理对数线性模型中 0 细胞计数的常用技术。

R 和 SPSS 为对数线性分析返回不同的参数

R and SPSS returning different parameters for loglinear analysis

r

spss