The length of a vector of yes/no answers has little to do with the number of 
possible responses (2). Factors keep both pieces of information.

If you only have yes responses in your data set, when converted to factor you 
would have to tell R that other responses  were possible.

I prefer to avoid working with factors until I need them.  Use the str function 
to investigate where factors are being introduced and either use options to 
keep the data as character or convert it back to character if you can't figure 
that out.
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Sent from my phone. Please excuse my brevity.

Sri krishna Devarayalu Balanagu <balanagudevaray...@gvkbio.com> wrote:

>Why the error is coming? even though the length of outcome.new$compkey
>and outcome.new$armkey were exactly same.
>Can anyone help?
>
>setwd("D:/AZ")
>library("RODBC")
>cdb_cnct <-
>odbcConnectExcel("AZIF_DC_GVK_NSCLC_MSALL_287papers_02072012_141450_v1_4.xls")
>outcomes <- sqlFetch(cdb_cnct, "Outcomes_info")
>odbcClose(cdb_cnct)
>rm(cdb_cnct)
>sink("Dependency checks.log")
>outcomes[(outcomes$Comparator != 9999), ] -> outcome
>compkey <- paste(outcome$Comparator, outcome$Comparator_Subarm,
>sep='_')
>armkey <- paste(outcome$Arm_ID, outcome$SubArm_ID, sep='_')
>outcome.new <- cbind(outcome, compkey, armkey)
>invalid.ids <- outcome.new[outcome.new$compkey == outcome.new$armkey,
>c("Assessment_record_ID")]
>
>Error in Ops.factor(outcome.new$compkey, outcome.new$armkey) :
>  level sets of factors are different
>
>
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