Output from the program is a text file. The first part of the output gives the results for each cell of the table. The second part of the output (unless suppressed by the NOMETADATA option) gives the metadata, in the form of DDL, for the variables used in the tables.
One line is output for each cell of the table. By default, cells with no actual cases are not output. With the ALLCELLS option, however, all cells of the table are output, PROVIDED that a category of each variable was actually encountered in the dataset. This means that categories that are theoretically possible to encounter because they are within the valid range of a variable, but were never in fact used in the data, still will not be output.
Examples of program input and output are given below.
This program can be run only in batch mode. It is not invoked through the regular SDA user interface.
Keyword Possible Specification Default (if no keyword) _____________________________________________________________________ STUdy= path of dataset directory Look for variables only in (can be repeated) current directory INVARs= name of var(s) to crosstab REQUIRED (can be repeated ) MEANvar= name of variable for means Generate frequencies Weight= name of weight variable No weighting Filter= name(s) and codes of filter No filter variable(s) SAvefile= filename to receive output Output sent to screen (overwrite existing file) (standard output) ALLCELls= yes Exclude cells with zero cases MDInclude= yes Exclude missing data codes NOMETAdata= yes Output metadata (DDL specs) for the variables in the tableNote that it is enough to mention the keywords ALLCELLS, MDINCLUDE, and NOMETADATA. They will be activated whether or not they are followed by ’= yes’.
Output from the preceding batch file (example 1)
# Location of SDA study (relative or absolute path) study = /sa/sdatest # Input variables - from 1 to 10 can be specified. invar = ideo invar = spend # Weight variable name weight = casewt # Filter specification. Multiple filters with multiple # codes and/or ranges can be specified filter = gender(1) # Filename for output (default is "standard output") savefile = out1.txt
Note in the output example above that the lines for the individual cells start with the ’invar’ (input variable) code values for the cell. The value in the first column is for the first ’invar’ (’ideo’). The second column is for the second ’invar’ (’spend’), and so on if there are more than two input variables.
CasesTotal = 1113 CasesValid = 473 InvarCount = 2 Invar = ideo Invar = spend Weight = casewt Filter = gender(1) # Contents of each cell: # Input variable values, N, weighted N CellsStart 1 1 : 117 115.823 1 3 : 41 41.369 1 5 : 4 3.206 3 1 : 58 66.546 3 3 : 66 81.190 3 5 : 14 12.505 5 1 : 96 94.551 5 3 : 70 73.224 5 5 : 7 5.772 CellsEnd CellsTotal = 9 DDLStart * name = ideo label = Political ideology in general type = numeric record = 1 column = 64 width = 1 max = 5 md = 8,9 catlabels = 1 Liberal 3 Conservative [Conserv] 5 Moderate 7 Never think of myself in those terms [Not labl] 8 Don’t know [DK] 9 Refused text = In general, when it comes to politics, do you usually think of yourself as a liberal, a conservative, a moderate, or what? * name = spend label = Military spending type = numeric record = 1 column = 40 width = 1 md = 8,9 catlabels = 1 Too much 3 About right [Abt ok] 5 Too little [Too litl] 8 Don’t know [DK] 9 Refused text = This country faces many problems, none of which can be solved easily or inexpensively. I’m going to name some of these problems. For each one, please tell me whether you think we’re spending too much money on them, too little money, or about the right amount. First, how about spending on the military, armaments, and defense? * name = casewt label = Overall sampling weight type = numeric record = 1 column = 11 width = 6 decimals = 3 text = (Overall sampling weight. This weight adjusts for sampling stratum, number of adults in the selected household, and the number of telephone lines into the selected household. The weight is scaled so that the total number of weighted cases equals the number of unweighted cases -- 1113.) * name = gender label = Gender of respondent type = numeric record = 1 column = 28 width = 1 catlabels = 1 Male 2 Female text = CODE OR ASK AS NEEDED: What sex are you? * DDLEnd
Then a colon is inserted to separate the ’invar’ code values from the cell counts.
The first number after the colon is the unweighted N. The second number is the weighted N. (If no weight variable is specified, the weighted N will just be the same as the unweighted N.)
In the output example shown above, the first cell has a value of 1 on the variable ’ideo’ and a value of 1 on ’spend’. The are 117 male cases with that combination of codes, and the weighted N of cases with that combination (using the weight variable ’casewt’) is 115.823.
If the ’meanvar’ keyword is specified in the batch file, the output format is somewhat different. Here is an example with a ’meanvar’ and also with the ’age’ invar temporarily recoded into 3 categories:
Output from the preceding batch file (example 2)study = /sa/sdatest # If a ’meanvar’ is specified, the output for each cell includes # not only counts, but also the mean for that variable in each cell. meanvar = spend invar = ideo # Age is temporarily recoded into 3 categories invar = age(r:1=*-30;2=31-50;3=51-*) weight = casewt filter = gender(1) # Suppress metadata (DDL specifications) in the output. nometadata = yes savefile = out2.txt
Note that each line documenting a cell’s contents now has two extra pieces of information: the numerator used to compute the mean of the specified ’meanvar’ (’spend’), and the mean itself (calculated by dividing the numerator by the weighted N in each cell).
CasesTotal = 1113 CasesValid = 472 InvarCount = 2 Invar = ideo Invar = age(r: 1 = *-30; 2 = 31-50; 3 = 51-*) Meanvar = spend Weight = casewt Filter = gender(1) # Contents of each cell: # Input variable values, N, weighted N, Numerator, Mean CellsStart 1 1 : 55 60.771 104.063 1.7123792598 1 2 : 78 72.049 99.307 1.3783258616 1 3 : 29 27.578 52.590 1.9069548191 3 1 : 45 56.227 147.513 2.6235260640 3 2 : 49 49.975 109.837 2.1978389195 3 3 : 43 52.756 111.442 2.1124042763 5 1 : 49 55.425 103.743 1.8717726658 5 2 : 85 81.884 156.926 1.9164427727 5 3 : 39 36.238 82.414 2.2742425079 CellsEnd CellsTotal = 9
|DDL||Data Description Language used by SDA Programs|
|tables||Main SDA crosstabulation program|