HI,
I guess your original dataset would have some list elements as empty.
Clean<- structure(list(GRADE = c(1, 2, 3, 1.5, 1.75, 2, 0.5, 2, 3.5,
3.5, 3.75, 4), TERM = c(9L, 9L, 9L, 8L, 8L, 8L, 9L, 9L, 9L, 8L,
8L, 8L), INST_NUM = c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L)), .Names = c("GRADE", "TERM", "INST_NUM"), class = "data.frame",
row.names = c(NA,
-12L))
lapply(split(Clean,list(Clean$TERM,Clean$INST_NUM)),function(x)
shapiro.test(x$GRADE))
#$`8.1`
# Shapiro-Wilk normality test
#
#data: x$GRADE
#W = 1, p-value = 1
#
#$`9.1`
#
# Shapiro-Wilk normality test
#
#data: x$GRADE
#W = 1, p-value = 1
-----------------------------------------------------
sapply(split(Clean,list(Clean$TERM,Clean$INST_NUM)),function(x)
shapiro.test(x$GRADE)$p.value)
#8.1 9.1 8.2 9.2
# 1 1 1 1
with(Clean, aggregate(GRADE,list(TERM,INST_NUM),FUN=shapiro.test)) #the output
is a list,
# Group.1 Group.2 x
#1 8 1 1
#2 9 1 1
#3 8 2 1
#4 9 2 1
#Warning message:
#In format.data.frame(x, digits = digits, na.encode = FALSE) :
# corrupt data frame: columns will be truncated or padded with NAs
library(plyr)
ldply(dlply(Clean,.(TERM,INST_NUM), function(x) shapiro.test(x$GRADE)),
summarize, pval=p.value)
# TERM INST_NUM pval
#1 8 1 1
#2 8 2 1
#3 9 1 1
#4 9 2 1
Now, consider this example:
Clean1<- structure(list(GRADE = c(1, 2, 3, 1.5, 1.75, 2, 0.5, 2, 3.5,
3.5, 3.75, 4, 4.5, 4.25, 4.32), TERM = c(9L, 9L, 9L, 8L, 8L,
8L, 9L, 9L, 9L, 8L, 8L, 8L, 10L, 10L, 10L), INST_NUM = c(1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L)), .Names = c("GRADE",
"TERM", "INST_NUM"), class = "data.frame", row.names = c(NA,
-15L))
lapply(split(Clean1,list(Clean1$TERM,Clean1$INST_NUM)),function(x)
shapiro.test(x$GRADE))
#Error in shapiro.test(x$GRADE) : sample size must be between 3 and 5000
split(Clean1,list(Clean1$TERM,Clean1$INST_NUM))[[6]] ###0 rows
#[1] GRADE TERM INST_NUM
#<0 rows> (or 0-length row.names)
lst1<-split(Clean1,list(Clean1$TERM,Clean1$INST_NUM))
lapply(lst1[lapply(lst1,nrow)>0], function(x) shapiro.test(x$GRADE))
#$`8.1`
#
# Shapiro-Wilk normality test
#
#data: x$GRADE
#W = 1, p-value = 1
You could do this directly with:
ldply(dlply(Clean1,.(TERM,INST_NUM), function(x) shapiro.test(x$GRADE)),
summarize, pval=p.value)
# TERM INST_NUM pval
#1 8 1 1.0000000
#2 8 2 1.0000000
#3 9 1 1.0000000
#4 9 2 1.0000000
#5 10 1 0.5248807
ldply(dlply(Clean1,.(TERM,INST_NUM), function(x) shapiro.test(x$GRADE)),
summarize, pval=p.value,stat1=statistic)
# TERM INST_NUM pval stat1
#1 8 1 1.0000000 1.0000000
#2 8 2 1.0000000 1.0000000
#3 9 1 1.0000000 1.0000000
#4 9 2 1.0000000 1.0000000
#5 10 1 0.5248807 0.9393788
#or
with(Clean1, aggregate(GRADE,list(TERM,INST_NUM),FUN=function(x)
shapiro.test(x)$p.value))
Group.1 Group.2 x
1 8 1 1.0000000
2 9 1 1.0000000
3 10 1 0.5248807
4 8 2 1.0000000
5 9 2 1.0000000
#If you want both pvalue and statistic
with(Clean1, aggregate(GRADE,list(TERM,INST_NUM),FUN=function(x)
cbind(shapiro.test(x)$p.value,shapiro.test(x)$statistic)) )
# Group.1 Group.2 x.1 x.2
#1 8 1 1.0000000 1.0000000
#2 9 1 1.0000000 1.0000000
#3 10 1 0.5248807 0.9393788
#4 8 2 1.0000000 1.0000000
#5 9 2 1.0000000 1.0000000
Hope this helps.
A.K.
________________________________
From: Robert Lynch <robert.b.ly...@gmail.com>
To: arun <smartpink...@yahoo.com>
Cc: R help <r-help@r-project.org>
Sent: Tuesday, August 20, 2013 8:00 PM
Subject: Re: [R] ave function
I tried
> lapply(split(Clean,list(Clean$TERM,Clean$INST_NUM)),function(x)
> shapiro.test(x$GRADE))
and I got
>Error in shapiro.test(x$GRADE.) : sample size must be between 3 and 5000
I also tried
with(Clean, aggregate(GRADE,list(TERM,INST_NUM),FUN=shapiro.test))
and got
Group.1 Group.2 x
1 201001 689809 0.9546164
2 201201 689809 0.9521624
3 201301 689809 0.9106206
4 200701 994474 0.8862705
5 200710 994474 0.9176743
6 201203 1105752 0.9382688
.
.
.
72 201001 1759272 0.9291295
73 201101 1759272 0.9347072
74 201110 1897809 0.9395375
Warning message:
In format.data.frame(x, digits = digits, na.encode = FALSE) :
corrupt data frame: columns will be truncated or padded with NAs
I am not sure how to interpret the output of the second.
Thanks!
On Tue, Aug 13, 2013 at 11:01 AM, arun <smartpink...@yahoo.com> wrote:
Hi,
>You could try:
> lapply(split(Clean,list(Clean$TERM,Clean$INST_NUM)),function(x)
>shapiro.test(x$GRADE))
>A.K.
>
>
>
>
>
>----- Original Message -----
>From: Robert Lynch <robert.b.ly...@gmail.com>
>To: r-help@r-project.org
>Cc:
>Sent: Tuesday, August 13, 2013 1:46 PM
>Subject: [R] ave function
>
>I've written the following function
>CoursePrep <- function (Source, SaveName) {
>
>
> Clean$TERM <- as.factor(Clean$TERM)
>
> Clean$INST_NUM <- as.factor(Clean$INST_NUM)
> Clean$zGrade <- with(Clean, ave(GRADE., list(TERM, INST_NUM), FUN =
>scale))
> write.csv(Clean,paste(SaveName, "csv", sep ="."), row.names = FALSE)
> return(Clean)
>}
>
>which is all well and good, but I wan't to throw a shapiro.test in before I
>normalize. that is I don't really understand quite how I did ( I got help)
>what I wanted to in the
>Clean$zGrade <- with(Clean, ave(GRADE., list(TERM, INST_NUM), FUN = scale))
>that code for the whole of Clean finds all sets of GRADE.'s that have the
>same INST_NUM and TERM computes a mean, subtracts off the mean and divides
>by the standard deviation. I would like to for each one of those sets of
>grades to call shapiro.test() on the set, to see if it is normal *before* I
>assume it is.
>
>I know the naive
>with(Clean, shapiro.test( list(TERM, INST_NUM)))
>doesn't work.
>with(Clean, ave(GRADE., list(TERM, INST_NUM), FUN =
>function(x)shapiro.test(x)))
>
>which returns
>Error in shapiro.test(x) : sample size must be between 3 and 5000
>and I have checked that the sets selected are all of length between 3 and
>5000.
>using the following on my full data
>
>ClassSize <- with(Clean, ave(GRADE., list(TERM, INST_NUM), FUN =
>function(x)length(x)))
>> summary(ClassSize)
> Min. 1st Qu. Median Mean 3rd Qu. Max.
> 22.0 198.0 241.0 244.4 279.0 466.0
>
>here is some sample data
>GRADE TERM INST_NUM
>1, 9, 1
>2, 9, 1
>3, 9, 1
>1.5, 8, 2
>1.75, 8, 2
>2, 8, 2
>0.5, 9, 2
>2, 9, 2
>3.5, 9, 2
>3.5, 8, 1
>3.75, 8, 1
>4, 8, 1
>
>and hopefully the code would test the following set of grades
>(1,2,3)(1.5,1.75,2)(0.5,2,3.5)(3.5,3.75,4)
>
>Thanks Robert
>
> [[alternative HTML version deleted]]
>
>______________________________________________
>R-help@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.
>
>
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
