From: sunny <sunayan_at_gmail.com>

Date: Sun, 08 May 2011 22:50:19 -0700 (PDT)

>> Not knowing what format your data is in or what model you are using...

*>>
*

*>> df # is your data frame with columns the variables you are running
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*>> regressions for
*

*>> datout <- data.frame(coeff = NA, conf_low = NA, conf_high = NA, odd = NA)
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*>> #
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*>> a table to put your results in
*

*>> for(i in 1:length(names(df)[2:10])) {
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*>> fit <- glm(data[,1] ~ data[,i], data = df, etc...)
*

*>> datout[i,] <- fit[e.g, 1:4] # determine what values in your model output
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*>> are what you need
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*>> }
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*>> datout # a table with all your output for each variable
*

*>>
*

*>> On Sunday, May 8, 2011 at 11:58 AM, SevannaD wrote:
*

*>>
*

*>> I have never made a loop on my own to do anything in R. But I am hoping
*

*>>
*

*>> > someone can help me build one for the following issue:
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*>> >
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*>> > I need to make a univariate logistic regression for each of my
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*>> variables
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*>> > (about 62 of them), then I need to gather up each of their coefficients
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*>> (not
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*>> > the intercepts), each of their 95% confidence intervals, and each of
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*>> thier
*

*>> > odds ratios and place them in a matrix to showcase them for my thesis.
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*>> >
*

*>> > currently, I am writing them all out one by one with the cbond method,
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*>> which
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*>> > has taken me a better part of a day so far and I know there has to be
*

*>> able
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*>> > to be a way to make a loop that can do this whole process, I just
*

*>> havent
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*>> > been able to figure it out yet.
*

*>> >
*

*>> > Thanks in advance.
*

*>> >
*

*>> > --
*

*>> > View this message in context:
*

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*>> > Sent from the R help mailing list archive at Nabble.com.
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*>> >
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>

Date: Sun, 08 May 2011 22:50:19 -0700 (PDT)

Maybe this is what you're looking for:

# x is your set of explanatory variables (10 of them): x <- array(rnorm(10000), dim=c(1000,10))

# y is your dependent variable:

y <- rbinom(1000, 1, 0.3)

# run the regression on each column of x: reg <- apply(x, 2, function(z) glm(y ~ z, family=binomial(link='logit')))

# the previous output is a list. Now collect whatever you need from each
list element:

bond <- lapply(reg, function(z) c(z$coeff[2], exp(z$coeff[2]),
confint(z)[2,], exp(confint(z)[2,])))

# collect everything together as a matrix:
bond <- do.call(rbind, bond)

bond

-S.

SevannaD wrote:

> > So in my first try before I got your message, this is what I did: > > orconf<-list() > ccoef<-list() > or<-list() > coef<-list() > out<-list() > for (i in 1:49){ > out[[i]]<-glm(y~var[[i]],family=binomial(link="logit")) > coef[[i]]<-out[[i]]$coef[2] > or[[i]]<-exp(out[[i]]$coef[2]) > bond<-matrix(out[[i]]$coef[2], > exp(out[[i]]$coef[2]),confint(out[[i]]$coef[2]),exp(confint(out[[i]]$coef[2]))) > } > But it did not work due to confint(out[[i]]$coef[2] and the exp one. Said > Error in object$coefficients : $ operator is invalid for atomic vectors. > > would I would to identify conf_low and conf_high as two separate things? > > Thanks > > On Sun, May 8, 2011 at 4:31 PM, Scott Chamberlain-3 [via R] < > ml-node+3508106-1763482049-235888_at_n4.nabble.com> wrote: >

>> Not knowing what format your data is in or what model you are using...

>

-- View this message in context: http://r.789695.n4.nabble.com/help-with-a-vector-loop-problem-tp3507366p3508483.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Mon 09 May 2011 - 06:05:46 GMT

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