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about TableSubgroupMultiGLM #35

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Licun1 opened this issue Jun 24, 2024 · 1 comment
Open

about TableSubgroupMultiGLM #35

Licun1 opened this issue Jun 24, 2024 · 1 comment

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@Licun1
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Licun1 commented Jun 24, 2024

TableSubgroupMultiCox(Surv(time, status) ~ sex, var_subgroups = c("kk", "kk1"), data = lung, line = TRUE)
Variable Count Percent Point Estimate Lower Upper sex=1 sex=2 P value P for interaction
sex Overall 228 100 1.91 1.14 3.2 100 100 0.014
1
2 kk 0.525
3 0 38 16.9 2.88 0.31 26.49 10 100 0.35
4 1 187 83.1 1.84 1.08 3.14 100 100 0.026
5
6 kk1 0.997
7 0 8 3.6 0 100
8 1 217 96.4 1.88 1.12 3.17 100 100 0.018
警告信息:
In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :
Loglik converged before variable 1,2,3 ; coefficient may be infinite.
TableSubgroupMultiGLM(status ~ sex, var_subgroups = c("kk", "kk1"), data = lung, family = "binomial")
[1] "binomial"

Thank you very much for providing this package. However, when I use the TableSubgroupMultiGLM function, it seems that the returned values are incorrect. But when I use the TableSubgroupMultiCox function, it returns the correct values. What's wrong with it?
@jinseob2kim
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I run TableSubgroupMultiGLM(status ~ sex, var_subgroups = c("kk", "kk1"), data = lung, family = “binomial”). The below is the result.

Could you show what that wrong result is ?

     Variable Count Percent           OR Lower Upper P value P for interaction
sex2  Overall   228     100         3.01  1.65  5.47  <0.001              <NA>
1          kk  <NA>    <NA>         <NA>  <NA>  <NA>      NA             0.476
2           0    38    16.9            7   0.7 70.03   0.098              <NA>
3           1   187    83.1         2.94  1.55  5.57   0.001              <NA>
4         kk1  <NA>    <NA>         <NA>  <NA>  <NA>      NA             0.984
5           0     8     3.6 314366015.19     0   Inf   0.997              <NA>
6           1   217    96.4         2.85  1.55  5.25   0.001              <NA>

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@jinseob2kim @Licun1