[R] Error in if (nuhat < 2) stop("The degrees of freedom must be greater than or equal to 2") : missing value where TRUE/FALSE needed

[Uwe Ligges]

As far as I understand you want:


lmo <- lm(Simon ~ TypeBiling + FAS, data = bilingualdataforconferences2012)

anova(lmo)
summary(lmo)

for the ordinary ancova.

Not sure if there is a proper implementation for that kind of 
"bootstrapped robust ancova" you are using. You may have to fix the code 
on the URL you cited.

In any case, looking at the data via some plots suggests that there is 
not too much in the data (at least given the three variables you are 
dealing with - not with ordinary ancova nor any other kind of method)

Uwe Ligges





On 30.04.2012 16:17, Kyriakos Antoniou wrote:
>
> Dear Uwe,
>
> really sorry about this.
>
> The code i use is the following (data attached again):
>
> setwd("C:/Users/User/Desktop/Rdatabilingualstudy2012")
>
> bilingualdataforconferences2012<-read.delim("bilingualdataforconferences2012.dat", header=TRUE)
>
> bilingualdataforconferences2012$TypeBiling<-factor(bilingualdataforconferences2012$TypeBiling, levels = c(0:1), labels = c("monolingual", "bilingual"))
>
> cypriot<-subset(bilingualdataforconferences2012, TypeBiling=="monolingual")
> cypriotenglish<-subset(bilingualdataforconferences2012, TypeBiling=="bilingual")
>
> covGrp1<-cypriot$FAS
> dvGrp1<-cypriot$Simon
> covGrp2<-cypriotenglish$FAS
> dvGrp2<-cypriotenglish$Simon
>
> source("http://www-rcf.usc.edu/~rwilcox/Rallfun-v16")
>
> ancova(covGrp1, dvGrp1, covGrp2, dvGrp2)
> ancboot(covGrp1, dvGrp1, covGrp2, dvGrp2, nboot = 2000)
>
> I am trying to run an ANCOVA and a bootstrapped ANCOVA analysis on the data set attached, using the ancova and ancboot functions as above.  That is, i want to see what the effect of bilingualism (variable TypeBiling, 1=bilingual, 2=monolingual) is on the dependent variable Simon when partialling out the effect of the covariate FAS (socioeconomic status).  Since the data for the dependent variable Simon are not normally distributed i need to also analyse the data using a robust method of ANCOVA.
>
> Kyriakos
>
>> Date: Mon, 30 Apr 2012 15:58:34 +0200
>> From: ligges at statistik.tu-dortmund.de
>> To: antoniouky at hotmail.com
>> CC: r-help at r-project.org
>> Subject: Re: [R] Error in if (nuhat<  2) stop("The degrees of freedom must be greater than or equal to 2") : missing value where TRUE/FALSE needed
>>
>>
>>
>> On 30.04.2012 15:52, Kyriakos Antoniou wrote:
>>>
>>> Sorry!!  Data now attached.  Note that this is a .dat file while in the R code i import data directly from an SPSS file (.sav).
>>
>>
>> Oh, come on, we do not have endless time to import your data, so
>> inlcuding code please.
>>
>> Moreover, you have not really described which model yopu want to fit
>> exactly, we can only guess from your code not knowing those functions
>> you used.
>>
>> Uwe Ligges
>>
>>
>>
>>> Best,
>>> Kyriakos
>>>
>>>> Date: Mon, 30 Apr 2012 15:20:04 +0200
>>>> From: ligges at statistik.tu-dortmund.de
>>>> To: antoniouky at hotmail.com
>>>> CC: r-help at r-project.org
>>>> Subject: Re: [R] Error in if (nuhat<   2) stop("The degrees of freedom must be greater than or equal to 2") : missing value where TRUE/FALSE needed
>>>>
>>>>
>>>>
>>>> On 29.04.2012 16:28, Kyriakos Antoniou wrote:
>>>>>
>>>>> Hi,
>>>>>
>>>>> i am trying to run an ANCOVA and a bootstrapped ANCOVA analysis on a specific data set.  I am using the ancova and ancboot functions as in the following code:
>>>>>
>>>>> setwd("C:/Users/User/Desktop/Rdatabilingualstudy2012")
>>>>>
>>>>> bilingualismdata<-read.spss("bilingualdataforconferences2012.sav", use.value.labels = TRUE, to.data.frame = TRUE)
>>>>>
>>>>> bilingualismdata$TypeBiling<-factor(bilingualismdata$TypeBiling, levels = c(0:1), labels = c("monolingual", "bilingual"))
>>>>>
>>>>> cypriot<-subset(bilingualismdata, TypeBiling=="monolingual")
>>>>> cypriotenglish<-subset(bilingualismdata, TypeBiling=="bilingual")
>>>>>
>>>>> covGrp1<-cypriot$FAS
>>>>> dvGrp1<-cypriot$Simon
>>>>> covGrp2<-cypriotenglish$FAS
>>>>> dvGrp2<-cypriotenglish$Simon
>>>>>
>>>>> source("http://www-rcf.usc.edu/~rwilcox/Rallfun-v16")
>>>>>
>>>>> ancova(covGrp1, dvGrp1, covGrp2, dvGrp2)
>>>>> ancboot(covGrp1, dvGrp1, covGrp2, dvGrp2, nboot = 2000)
>>>>>
>>>>>
>>>>> However, i always get the following errors (note that i get these errors when i am running the analysis on a specific data set.  The same code works fine with other data sets):
>>>>>
>>>>>> ancova(covGrp1, dvGrp1, covGrp2, dvGrp2)
>>>>> [1] "NOTE: Confidence intervals are adjusted to control the probability"
>>>>> [1] "of at least one Type I error."
>>>>> [1] "But p-values are not"
>>>>> Error in if (nuhat<    2) stop("The degrees of freedom must be greater than or equal to 2") :
>>>>>      missing value where TRUE/FALSE needed
>>>>
>>>> Aleady the way the Note is printed shows the code is poorly written, the
>>>> non-working error message supports that.
>>>> Since we do not have the data, we cannot help, probably lm() is capable
>>>> of the ancova you have in mind.
>>>>
>>>> Uwe Ligges
>>>>
>>>>
>>>>
>>>>
>>>>> In addition: Warning messages:
>>>>> 1: In min(sub[vecn>= 12]) :
>>>>>      no non-missing arguments to min; returning Inf
>>>>> 2: In max(sub[vecn>= 12]) :
>>>>>      no non-missing arguments to max; returning -Inf
>>>>> 3: In near(x1, x1[isub[i]], fr1) : NAs introduced by coercion
>>>>> 4: In near(x2, x1[isub[i]], fr2) : NAs introduced by coercion
>>>>> 5: NAs introduced by coercion
>>>>>
>>>>>> ancboot(covGrp1, dvGrp1, covGrp2, dvGrp2, nboot = 2000)
>>>>> [1] "Note: confidence intervals are adjusted to control FWE"
>>>>> [1] "But p-values are not adjusted to control FWE"
>>>>> [1] "Taking bootstrap samples. Please wait."
>>>>> Error in if (nuhat<    2) stop("The degrees of freedom must be greater than or equal to 2") :
>>>>>      missing value where TRUE/FALSE needed
>>>>> In addition: Warning messages:
>>>>> 1: In min(sub[vecn>= 12]) :
>>>>>      no non-missing arguments to min; returning Inf
>>>>> 2: In max(sub[vecn>= 12]) :
>>>>>      no non-missing arguments to max; returning -Inf
>>>>> 3: In near(x1, x1[isub[i]], fr1) : NAs introduced by coercion
>>>>> 4: In near(x2, x1[isub[i]], fr2) : NAs introduced by coercion
>>>>> 5: In near(x1, x1[isub[i]], fr1) : NAs introduced by coercion
>>>>> 6: In near(x2, x1[isub[i]], fr2) : NAs introduced by coercion
>>>>>
>>>>> Any help with how i van solve this would be appreciated as i am really stack and don't really know what to do.
>>>>>
>>>>> Best,
>>>>> Kyriakos
>>>>
>>>> [irrelevant part deleted]
>>>>
>>>>> ______________________________________________
>>>>> 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.
>>>    		 	   		
>