Re: [R] Question about cochran test in R

2015-05-08 Thread Henric Winell

Hi Luis,

(Let's keep R-help in the loop for the benefit of others.)

On 2015-05-08 10:25, Luis Fernando García wrote:


Thanks a lot for your replies Henry!

Your answer was specially a bless! Many thanks this was an issue which
was breaking my head.

I have another couple of questions, may be you could help me. For post
hoc comparison I was planning to run a McNemar test with a bonferroni
correction, but wanted to be sure my approach is correct.


It's an OK approach, I guess, but you should use the Holm correction 
rather than Bonferroni.  (Holm dominates Bonferroni and is valid under 
the same arbitrary assumptions.)


The classical approach, and as suggested in Cochran (1950), would be 
to partition the chi-squared statistic into components of interest.


In a more general approach, a test of all the post-hoc comparisons is 
performed simultaneously.  This is very efficient, in terms of power, 
since it takes account of the correlation between the test statistics. 
Ignoring such dependencies may result in strange results, due to loss 
of power, where none of the partial null hypotheses are rejected even 
though the global null hypothesis is rejected.  Unfortunately, I'm not 
aware of any publicly available software that let's you do this.  In 
theory, 'coin' should be able to, and there has even been some work done 
in this direction, but it's currently unfinished.



Henric Winell





Sorry if I annoy you with this remaining question.

Thanks in advance!

2015-05-07 8:03 GMT-03:00 Henric Winell nilsson.hen...@gmail.com
mailto:nilsson.hen...@gmail.com:

On 2015-05-07 09:15, Jim Lemon wrote:

Hi Luis,
Try this page:

http://www.r-bloggers.com/cochran-q-test-for-k-related-samples-in-r/

Jim


Cochran's Q test is a marginal homogeneity test, and such tests can
be performed by the 'mh_test' function in the 'coin' package.  The
following replicates the result in the blog post

  library(coin)
 
  dta - data.frame(
+ method= factor(rep(LETTERS[1:4], 6)),
+ repellent = factor(c(1, 1, 0, 0,
+  1, 1, 0, 1,
+  1, 0, 0, 0,
+  1, 1, 1, 0,
+  1, 1, 0, 1,
+  1, 1, 0, 1)),
+ fabric= gl(6, 4, labels = as.roman(1:6))
+ )
 
  mh_test(repellent ~ method | fabric, data = dta)

 Asymptotic Marginal-Homogeneity Test

data:  repellent by
  method (A, B, C, D)
  stratified by fabric
chi-squared = 9.3158, df = 3, p-value = 0.02537


and uses the asymptotic approximation to compute the p-value.  The
'coin' package also allows you to approximate the exact null
distribution using Monte Carlo methods:

  set.seed(123)
  mh_test(repellent ~ method | fabric, data = dta,
+ distribution = approximate(B = 1L))

 Approximative Marginal-Homogeneity Test

data:  repellent by
  method (A, B, C, D)
  stratified by fabric
chi-squared = 9.3158, p-value = 0.0202


For future reference, 'mh_test' is fairly general and handles both
matched pairs or matched sets.  So, the well-known tests due
McNemar, Cochran, Stuart(-Maxwell) and Madansky are just special cases.

For more general symmetry test problems, the 'coin' package offers
the 'symmetry_test' function and this can be used to perform, e.g.,
multivariate marginal homogeneity tests like the multivariate
McNemar test (Klingenberg and Agresti, 2006) or the multivariate
Friedman test (Gerig, 1969).


Henric






On Thu, May 7, 2015 at 4:59 PM, Luis Fernando García
luysgar...@gmail.com mailto:luysgar...@gmail.com wrote:

Dear R Experts,

May be this is a basic question for you, but it is something
I need really
urgently. I need to perform a Chi Square analysis for more
than two groups
of paired observations. It seems to be ok For Cochran test.
Unfortunately I
have not found info about  this test in R, except for
dealing with outliers
which is not my aim. I am looking for something like this
https://www.medcalc.org/manual/cochranq.php

I found a video to perform this analysis in R, but was not
specially
useful. Does some of you know have some info about how to
make this
analysis in R?

Thanks in advance!

  [[alternative HTML version deleted]]

__
R-help@r-project.org mailto:R-help@r-project.org mailing
list -- To UNSUBSCRIBE and more, see
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[R] Question about cochran test in R

2015-05-07 Thread Luis Fernando García
Dear R Experts,

May be this is a basic question for you, but it is something I need really
urgently. I need to perform a Chi Square analysis for more than two groups
of paired observations. It seems to be ok For Cochran test. Unfortunately I
have not found info about  this test in R, except for dealing with outliers
which is not my aim. I am looking for something like this
https://www.medcalc.org/manual/cochranq.php

I found a video to perform this analysis in R, but was not specially
useful. Does some of you know have some info about how to make this
analysis in R?

Thanks in advance!

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.


Re: [R] Question about cochran test in R

2015-05-07 Thread Jim Lemon
Hi Luis,
Try this page:

http://www.r-bloggers.com/cochran-q-test-for-k-related-samples-in-r/

Jim


On Thu, May 7, 2015 at 4:59 PM, Luis Fernando García
luysgar...@gmail.com wrote:
 Dear R Experts,

 May be this is a basic question for you, but it is something I need really
 urgently. I need to perform a Chi Square analysis for more than two groups
 of paired observations. It seems to be ok For Cochran test. Unfortunately I
 have not found info about  this test in R, except for dealing with outliers
 which is not my aim. I am looking for something like this
 https://www.medcalc.org/manual/cochranq.php

 I found a video to perform this analysis in R, but was not specially
 useful. Does some of you know have some info about how to make this
 analysis in R?

 Thanks in advance!

 [[alternative HTML version deleted]]

 __
 R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
 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.

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.

Re: [R] Question about cochran test in R

2015-05-07 Thread Henric Winell

On 2015-05-07 09:15, Jim Lemon wrote:


Hi Luis,
Try this page:

http://www.r-bloggers.com/cochran-q-test-for-k-related-samples-in-r/

Jim


Cochran's Q test is a marginal homogeneity test, and such tests can be 
performed by the 'mh_test' function in the 'coin' package.  The 
following replicates the result in the blog post


 library(coin)

 dta - data.frame(
+ method= factor(rep(LETTERS[1:4], 6)),
+ repellent = factor(c(1, 1, 0, 0,
+  1, 1, 0, 1,
+  1, 0, 0, 0,
+  1, 1, 1, 0,
+  1, 1, 0, 1,
+  1, 1, 0, 1)),
+ fabric= gl(6, 4, labels = as.roman(1:6))
+ )

 mh_test(repellent ~ method | fabric, data = dta)

Asymptotic Marginal-Homogeneity Test

data:  repellent by
 method (A, B, C, D)
 stratified by fabric
chi-squared = 9.3158, df = 3, p-value = 0.02537


and uses the asymptotic approximation to compute the p-value.  The 
'coin' package also allows you to approximate the exact null 
distribution using Monte Carlo methods:


 set.seed(123)
 mh_test(repellent ~ method | fabric, data = dta,
+ distribution = approximate(B = 1L))

Approximative Marginal-Homogeneity Test

data:  repellent by
 method (A, B, C, D)
 stratified by fabric
chi-squared = 9.3158, p-value = 0.0202


For future reference, 'mh_test' is fairly general and handles both 
matched pairs or matched sets.  So, the well-known tests due McNemar, 
Cochran, Stuart(-Maxwell) and Madansky are just special cases.


For more general symmetry test problems, the 'coin' package offers the 
'symmetry_test' function and this can be used to perform, e.g., 
multivariate marginal homogeneity tests like the multivariate McNemar 
test (Klingenberg and Agresti, 2006) or the multivariate Friedman test 
(Gerig, 1969).



Henric






On Thu, May 7, 2015 at 4:59 PM, Luis Fernando García
luysgar...@gmail.com wrote:

Dear R Experts,

May be this is a basic question for you, but it is something I need really
urgently. I need to perform a Chi Square analysis for more than two groups
of paired observations. It seems to be ok For Cochran test. Unfortunately I
have not found info about  this test in R, except for dealing with outliers
which is not my aim. I am looking for something like this
https://www.medcalc.org/manual/cochranq.php

I found a video to perform this analysis in R, but was not specially
useful. Does some of you know have some info about how to make this
analysis in R?

Thanks in advance!

 [[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.


__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.



__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.