Description Usage Arguments Value Examples
Significant Cutoff Value for Cox Regression
1 2 |
data |
data |
time |
name for time variable |
y |
name for y, must be coded as 1 and 0. The outcome must be 1 |
x |
name for x |
cut.numb |
number of cutoff points |
n.per |
the least percentage of the smaller group comprised in all patients |
y.per |
the least percentage of the smaller outcome patients comprised in each group |
p.cut |
cutoff of p value, default is 0.05 |
strict |
logical. TRUE means significant differences for each group combination were considered. FALSE means considering for any combination |
include |
direction of cutoff point. Any left letter of lower or upper |
round |
digital. Default is 2 |
adjust |
numeric value, adjust methord for p value. 1, defaulted, represents Bonferroni. 2 represent formula given by Douglas G in 1994 |
a dataframe contains cutoff points value, subject numbers in each group, dumb variable, beta of regression and p value.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
1: all combination: 406
2: filter by n.per
----
====
Combination: 30
3: filter by y.per
Combination: 6
4: last combination: 3
cut1 cut2 n n.per y y.per dump hr
1 2.62 3.52 9/13/10 0.28/0.41/0.31 8/4/1 0.89/0.31/0.10 b2/b3 0.06/0.01
2 2.77 3.52 10/12/10 0.31/0.38/0.31 9/3/1 0.90/0.25/0.10 b2/b3 0.05/0.01
3 2.78 3.52 11/11/10 0.34/0.34/0.31 10/2/1 0.91/0.18/0.10 b2/b3 0.02/0.01
pvalue p.adjust
1 0.00/0.00 0.00/0.00
2 0.00/0.00 0.00/0.00
3 0.00/0.00 0.00/0.00
1: all combination: 406
2: filter by n.per
----
====
Combination: 30
3: filter by y.per
Combination: 6
4: last combination: 3
cut1 cut2 n n.per y y.per dump hr
1 2.62 3.52 9/13/10 0.28/0.41/0.31 8/4/1 0.89/0.31/0.10 b2/b3 0.06/0.01
2 2.77 3.52 10/12/10 0.31/0.38/0.31 9/3/1 0.90/0.25/0.10 b2/b3 0.05/0.01
3 2.78 3.52 11/11/10 0.34/0.34/0.31 10/2/1 0.91/0.18/0.10 b2/b3 0.02/0.01
pvalue p.adjust
1 0.00/0.00 0.00/0.00
2 0.00/0.00 0.00/0.00
3 0.00/0.00 0.00/0.00
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