Dear all,
I have a data frame with a status column and some condition columns. (a dput
of part of it is listed below).
I would like to know if:
1) There are more chances to have a "status" of "1" when more than one
conditions have the value of "1" ?
2) The "status" column is depending on any one or a combination of the
condition columns
Say, do I have a status of "1" whenever condition 2 & 3 (or only condition
2) are met ?
Do you know what type of analysis one can use to do that ?
Thanks in advance,
P
dput(df)
structure(list(status = c(0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L), cond.1 = c(0L, 0L, 0L, 1L,
0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L,
1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L), cond.2 = c(1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L,
1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
1L), cond.3 = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L,
0L, 0L, 1L, 0L, 0L, 0L), cond.4 = c(0L, 0L, 0L, 1L, 0L, 1L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), cond.5 = c(0L, 0L,
0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
)), .Names = c("status", "cond.1", "cond.2", "cond.3", "cond.4",
"cond.5"), row.names = c(NA, -50L), class = "data.frame")
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dependent column(s) in data frame
7 messages · PIKAL Petr, David Winsemius, PQuery
Hi You probably will get more answers when you post your question to Crossvalidated or Stackoverflow as it is more about statistics than about R. Petr
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of PQuery
Sent: Wednesday, February 19, 2014 8:20 PM
To: r-help at r-project.org
Subject: [R] dependent column(s) in data frame
Dear all,
I have a data frame with a status column and some condition columns. (a
dput
of part of it is listed below).
I would like to know if:
1) There are more chances to have a "status" of "1" when more than one
conditions have the value of "1" ?
2) The "status" column is depending on any one or a combination of the
condition columns
Say, do I have a status of "1" whenever condition 2 & 3 (or only
condition
2) are met ?
Do you know what type of analysis one can use to do that ?
Thanks in advance,
P
dput(df)
structure(list(status = c(0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L), cond.1 = c(0L, 0L, 0L, 1L,
0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L,
1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L), cond.2 = c(1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L,
1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
1L), cond.3 = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L,
0L, 0L, 1L, 0L, 0L, 0L), cond.4 = c(0L, 0L, 0L, 1L, 0L, 1L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), cond.5 = c(0L, 0L,
0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
)), .Names = c("status", "cond.1", "cond.2", "cond.3", "cond.4",
"cond.5"), row.names = c(NA, -50L), class = "data.frame")
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Hi, Thanks for the reply, I will wait a couple of days and eventually post elsewhere unless I find the solution myself. Best. -- View this message in context: http://r.789695.n4.nabble.com/dependent-column-s-in-data-frame-tp4685561p4685633.html Sent from the R help mailing list archive at Nabble.com.
On Feb 19, 2014, at 11:19 AM, PQuery wrote:
Dear all,
I have a data frame with a status column and some condition columns. (a dput
of part of it is listed below).
I would like to know if:
1) There are more chances to have a "status" of "1" when more than one
conditions have the value of "1" ?
2) The "status" column is depending on any one or a combination of the
condition columns
Say, do I have a status of "1" whenever condition 2 & 3 (or only condition
2) are met ?
Do you know what type of analysis one can use to do that ?
Thanks in advance,
P
dput(df)
structure(list(status = c(0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L), cond.1 = c(0L, 0L, 0L, 1L,
0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L,
1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L), cond.2 = c(1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L,
1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
1L), cond.3 = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L,
0L, 0L, 1L, 0L, 0L, 0L), cond.4 = c(0L, 0L, 0L, 1L, 0L, 1L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), cond.5 = c(0L, 0L,
0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
)), .Names = c("status", "cond.1", "cond.2", "cond.3", "cond.4",
"cond.5"), row.names = c(NA, -50L), class = "data.frame")
with(df, table(status=status, comb23 = cond.2&cond.3) )
comb23
status FALSE TRUE
0 33 1
1 11 5
The more general approach to analyzing binary responses is logistic regression.
-- David.
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David Winsemius Alameda, CA, USA
Many thanks David, I will have a look on logistic regression for my case. Do you know about a good example regarding logistic regression ? I was thinking also of using Multiple Factor Analysis too (MFA - like in FactoMineR). However I am not sure how successful this is going to be. Best, P. -- View this message in context: http://r.789695.n4.nabble.com/dependent-column-s-in-data-frame-tp4685561p4685684.html Sent from the R help mailing list archive at Nabble.com.
On Feb 22, 2014, at 4:28 AM, PQuery wrote:
Many thanks David, I will have a look on logistic regression for my case. Do you know about a good example regarding logistic regression ? I was thinking also of using Multiple Factor Analysis too (MFA - like in FactoMineR). However I am not sure how successful this is going to be.
Your data (exclusively 0/1 values) did not look like it would be suitable for factor analysis. Perhaps you mean to use that package's correspondence analysis methods?
David Winsemius Alameda, CA, USA
1 day later
Well I first thought of using the MFA by considering my data as categorical but indeed the correspondence analysis methods are better suitable for my data structure, Thanks again, P -- View this message in context: http://r.789695.n4.nabble.com/dependent-column-s-in-data-frame-tp4685561p4685734.html Sent from the R help mailing list archive at Nabble.com.