## NAME

spearman -- Compute the generalized Spearman's rho correlation coefficient.

## USAGE

`spearman input`

## DESCRIPTION

The `spearman` task computes the generalized Spearman's rank order
correlation coefficient between two variables. It can treat mixed
censoring including censoring in the independent variable, but can
have only one independent variable. It is not known how this method
responds to ties in the data. However, there is no reason to believe
that it is more accurate than Kendall's tau in this case, and it
should also used be with caution in the presence of tied values.

The test assumes the null hypothesis. The probability given by this program is the probability that there is no correlation between the variables. If the probability is small, that means "the probability that these two variables are not correlated is small" or approximately "these variables are correlated". If you see the result 0.000, it means "< 0.001".

The usual Spearman's rho correlation estimate for uncensored data is
simply the correlation between the ranks of the independent and
dependent variables. In order to extend the procedure to censored
data, the Kaplan-Meier estimate of the survival curve is used to
assign ranks to the observations. Consequently, the ranks assigned to
the observations may not be whole numbers. Censored points are
assigned half (for left-censored) or twice (for right-censored) the
rank that they would have had were they uncensored. This method is
based on preliminary findings and has not been carefully scrutinized
either theoretically or empirically. It is offered in the code to
serve as a less computer intensive approximation to the Kendall's tau
correlation, which becomes computationally infeasible for large data
sets. The generalized Spearman's Rho routine is not dependable for
small data sets (n < 30). In that situation the generalized Kendall's
tau routine (`bhkmethod`) should be relied upon.

## PARAMETERS

- input [string]
- Input file(s); this can be a list of files. Following each file name
is a list of column names in brackets. Thes column names specify which
columns in the file contain the information used by this task. The
brackets MUST contain three names in the following format:
[censor_indicator, independent_var, dependent_var]. The censor
indicator specifies the censorship of the data point. The different
kinds of censorship are explained in the
`censor`help file. The second name in the brackets specifies the column containing the independent variable. The third name specifies the column containing the dependent variable. If the input file is an STSDAS table, the names in brackets are the table column names. If the input file is a text file, the names in brackets are the column numbers. A title string will be printed if the input file is a table containing the header parameter`TITLE`.

- (verbose = no) [boolean]
- Provide detailed output?
The detailed output includes the number of data points and the number of censored points and type of censorship.

## EXAMPLES

1. Sequentially process several files. The following will compute the bhk correlation for the two files indicated. The first is an STSDAS table, and the second is a text file.

st> spearman kriss.tab[Censor,LogL2500A,LogL2keV],iraslum.dat[1,2,3]The above command will apply the

`spearman`task to the data in the table "kriss.tab", using the columns "Censor" for the censoring indicator, "LogL2500A" for the independent variable column, and "LogL2keV" for the dependent variable column. Then use the file "iraslum.dat" (text file), columns 1, 2, and 3 (censor, independent, dependent).

## BUGS

## SEE ALSO

censor, survival

Type "help statistics option=sys" for a higher-level description of
the `statistics` package.