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Home/ Questions/Q 925483
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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T19:31:37+00:00 2026-05-15T19:31:37+00:00

I have a problem using data from a tab delimited data file imported with

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I have a problem using data from a tab delimited data file imported with read.delim.

Most of the columns contain numerical data which I need to do a t.test for. Unfortunately I always get this error:

Error in if (stderr < 10 * .Machine$double.eps * max(abs(mx), abs(my))) 
            stop("data are essentiallyconstant") :
missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In mean.default(x) : argument is not numeric or logical: returning NA
2: In mean.default(y) : argument is not numeric or logical: returning NA

I noticed that this only happens with vectors that consist of different levels.
It won’t even perform simple numerical operations like vector[1] + vector[2] for leveled vectors.
Vectors without levels work fine, though.

How can I use the data in the leveled vectors for calculation?

Thank you

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-15T19:31:38+00:00Added an answer on May 15, 2026 at 7:31 pm

    I have been able to reproduce your error message with the following small example:

    x = as.factor(1:5)
    y = as.factor(1:5)
    
    t.test(x, y)
    

    yields

    Error in if (stderr < 10 * .Machine$double.eps * max(abs(mx), abs(my))) stop("data are essentially constant") : 
      missing value where TRUE/FALSE needed
    In addition: Warning messages:
    1: In mean.default(x) : argument is not numeric or logical: returning NA
    2: In mean.default(y) : argument is not numeric or logical: returning NA
    

    The problem is you are trying to perform a t-test on non-numeric vectors. Addition likewise is not defined for factors:

    x + y
    

    yields

    [1] NA NA NA NA NA
    Warning message:
    In Ops.factor(x, y) : + not meaningful for factors
    

    The warning gives keen insight as to what is amiss and also explains why your t-test is not working.

    To fix the problem, you need to do as ilya suggests: convert your vectors to numeric with as.numeric(as.character())

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