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Results

• the SAS log

• return codes stored in the automatic macro SYSINFO

• procedure output

• output data sets.

SAS Log

When you use the WARNING, PRINTALL, or ERROR option, PROC COMPARE writes a description of the differences to the SAS log.

Macro Return Codes (SYSINFO)

PROC COMPARE stores a return code in the automatic macro variable SYSINFO. The value of the return code provides information about the result of the comparison. By checking the value of SYSINFO after PROC COMPARE has run and before any other step begins, SAS macros can use the results of a PROC COMPARE step to determine what action to take or what parts of a SAS program to execute.

Macro Return Codes is a key for interpreting the SYSINFO return code from PROC COMPARE. For each of the conditions listed, the associated value is added to the return code if the condition is true. Thus, the SYSINFO return code is the sum of the codes listed in Macro Return Codes for the applicable conditions:

Macro Return Codes

Bit		Condition	Code	Hex	Description
1		DSLABEL	1	0001X	Data set labels differ
2		DSTYPE	2	0002X	Data set types differ
3		INFORMAT	4	0004X	Variable has different informat
4		FORMAT	8	0008X	Variable has different format
5		LENGTH	16	0010X	Variable has different length
6		LABEL	32	0020X	Variable has different label
7		BASEOBS	64	0040X	Base data set has observation not in comparison
8		COMPOBS	128	0080X	Comparison data set has observation not in base
9		BASEBY	256	0100X	Base data set has BY group not in comparison
10		COMPBY	512	0200X	Comparison data set has BY group not in base
11		BASEVAR	1024	0400X	Base data set has variable not in comparison
12		COMPVAR	2048	0800X	Comparison data set has variable not in base
13		VALUE	4096	1000X	A value comparison was unequal
14		TYPE	8192	2000X	Conflicting variable types
15		BYVAR	16384	4000X	BY variables do not match
16		ERROR	32768	8000X	Fatal error: comparison not done

These codes are ordered and scaled to allow a simple check of the degree to which the data sets differ. For example, if you want to check that two data sets contain the same variables, observations, and values, but you do not care about differences in labels, formats, and so forth, use the following statements:

proc compare base=SAS-data-set
             compare=SAS-data-set;
run;

%if &sysinfo >= 64 %then
   %do;
      handle error;
   %end;

You can examine individual bits in the SYSINFO value by using DATA step bit-testing features to check for specific conditions. For example, to check for the presence of observations in the base data set that are not in the comparison data set, use the following statements:

proc compare base=SAS-data-set
             compare=SAS-data-set;
run;

%let rc=&sysinfo;
data _null_;
   if &rc='1......'b then
      put 'Observations in Base but not
           in Comparison Data Set';
run;

PROC COMPARE must run before you check SYSINFO and you must obtain the SYSINFO value before another SAS step starts because every SAS step resets SYSINFO.

Procedure Output

The following sections show and describe the default output of the two data sets shown in Overview . Because PROC COMPARE produces lengthy output, the output is presented in seven pieces.

Data Set Summary

• the data set names

• the data set types, if any

• the data set labels, if any

• the dates created and last modified

• the number of variables in each data set

• the number of observations in each data set.

Partial Output shows the Data Set Summary.

Partial Output

COMPARE Procedure Comparison of PROCLIB.ONE with PROCLIB.TWO (Method=EXACT) Data Set Summary Dataset Created Modified NVar NObs Label PROCLIB.ONE 11SEP97:15:11:07 11SEP97:15:11:09 5 4 First Data Set PROCLIB.TWO 11SEP97:15:11:10 11SEP97:15:11:10 6 5 Second Data Set

Variables Summary

• the number of variables the data sets have in common

• the number of variables in the base data set that are not in the comparison data set and vice versa

• the number of variables in both data sets that have different types

• the number of variables that differ on other attributes (length, label, format, or informat)

• the number of BY, ID, VAR, and WITH variables specified for the comparison.

The second part of the report lists matching variables with different attributes and shows how the attributes differ. (The COMPARE procedure omits variable labels if the line size is too small for them.)

Partial Output shows the Variables Summary.

Partial Output

Variables Summary Number of Variables in Common: 5. Number of Variables in PROCLIB.TWO but not in PROCLIB.ONE: 1. Number of Variables with Conflicting Types: 1. Number of Variables with Differing Attributes: 3. Listing of Common Variables with Conflicting Types Variable Dataset Type Length student PROCLIB.ONE Num 8 PROCLIB.TWO Char 8 Listing of Common Variables with Differing Attributes Variable Dataset Type Length Format Label year PROCLIB.ONE Char 8 Year of Birth PROCLIB.TWO Char 8 state PROCLIB.ONE Char 8 PROCLIB.TWO Char 8 Home State gr1 PROCLIB.ONE Num 8 4.1 PROCLIB.TWO Num 8 5.2

Observation Summary

• the number of observations that the data sets have in common

• the number of observations in the base data set that are not in the comparison data set and vice versa

• the total number of observations in each data set

• the number of matching observations for which PROC COMPARE judged some variables unequal

• the number of matching observations for which PROC COMPARE judged all variables equal.

Partial Output shows the Observation Summary.

Partial Output

Observation Summary Observation Base Compare First Obs 1 1 First Unequal 1 1 Last Unequal 4 4 Last Match 4 4 Last Obs . 5 Number of Observations in Common: 4. Number of Observations in PROCLIB.TWO but not in PROCLIB.ONE: 1. Total Number of Observations Read from PROCLIB.ONE: 4. Total Number of Observations Read from PROCLIB.TWO: 5. Number of Observations with Some Compared Variables Unequal: 4. Number of Observations with All Compared Variables Equal: 0.

Values Comparison Summary

• the number of variables compared with all observations equal

• the number of variables compared with some observations unequal

• the number of variables with differences involving missing values, if any

• the total number of values judged unequal

• the maximum difference measure between unequal values for all pairs of matching variables (for differences not involving missing values).

In addition, for the variables for which some matching observations have unequal values, the report lists

• the name of the variable

• other variable attributes

• the number of times PROC COMPARE judged the variable unequal

• the maximum difference measure found between values (for differences not involving missing values)

• the number of differences caused by comparison with missing values, if any.

Partial Output shows the Values Comparison Summary.

Partial Output

Values Comparison Summary Number of Variables Compared with All Observations Equal: 1. Number of Variables Compared with Some Observations Unequal: 3. Total Number of Values which Compare Unequal: 6. Maximum Difference: 20. Variables with Unequal Values Variable Type Len Compare Label Ndif MaxDif state CHAR 8 Home State 2 gr1 NUM 8 2 1.000 gr2 NUM 8 2 20.000

Value Comparison Results

• the number of the observation or, if you use the ID statement, the values of the ID variables

• the value of the variable in the base data set

• the value of the variable in the comparison data set

• the difference between these two values (numeric variables only)

• the percent difference between these two values (numeric variables only).

Partial Output

Value Comparison Results for Variables __________________________________________________________ || Home State || Base Value Compare Value Obs || state state ________ || ________ ________ || 2 || MD MA 4 || MA MD __________________________________________________________ __________________________________________________________ || Base Compare Obs || gr1 gr1 Diff. % Diff ________ || _________ _________ _________ _________ || 1 || 85.0 84.00 -1.0000 -1.1765 3 || 78.0 79.00 1.0000 1.2821 __________________________________________________________ __________________________________________________________ || Base Compare Obs || gr2 gr2 Diff. % Diff ________ || _________ _________ _________ _________ || 3 || 72.0000 73.0000 1.0000 1.3889 4 || 94.0000 74.0000 -20.0000 -21.2766 __________________________________________________________

You can suppress the value comparison results with the NOVALUES option. If you use both the NOVALUES and TRANSPOSE options, PROC COMPARE lists for each observation the names of the variables with values judged unequal but does not display the values and differences.

Table of Summary Statistics

Note:    In all cases PROC COMPARE calculates the summary statistics based on all matching observations that do not contain missing values, not just on those containing unequal values.  
Partial Output shows the following summary statistics for base data set values, comparison data set values, differences, and percent differences:

N

the number of nonmissing values

MEAN

the mean, or average, of the values

STD

the standard deviation

MAX

the maximum value

MIN

the minimum value

STDERR

the standard error of the mean

T

the T ratio (MEAN/STDERR)

PROB> | T |

the probability of a greater absolute T value if the true population mean is 0.

NDIF

the number of matching observations judged unequal, and the percent of the matching observations that were judged unequal.

DIFMEANS

the difference between the mean of the base values and the mean of the comparison values. This line contains three numbers. The first is the mean expressed as a percentage of the base values mean. The second is the mean expressed as a percentage of the comparison values mean. The third is the difference in the two means (the comparison mean minus the base mean).

R

the correlation of the base and comparison values for matching observations that are nonmissing in both data sets.

RSQ

the square of the correlation of the base and comparison values for matching observations that are nonmissing in both data sets.

Partial Output is from the ALLSTATS option using the two data sets shown in "Overview":

Partial Output

Value Comparison Results for Variables __________________________________________________________ || Base Compare Obs || gr1 gr1 Diff. % Diff ________ || _________ _________ _________ _________ || 1 || 85.0 84.00 -1.0000 -1.1765 3 || 78.0 79.00 1.0000 1.2821 ________ || _________ _________ _________ _________ || N || 4 4 4 4 Mean || 85.5000 85.5000 0 0.0264 Std || 5.8023 5.4467 0.8165 1.0042 Max || 92.0000 92.0000 1.0000 1.2821 Min || 78.0000 79.0000 -1.0000 -1.1765 StdErr || 2.9011 2.7234 0.4082 0.5021 t || 29.4711 31.3951 0.0000 0.0526 Prob>|t| || <.0001 <.0001 1.0000 0.9614 || Ndif || 2 50.000% DifMeans || 0.000% 0.000% 0 r, rsq || 0.991 0.983 __________________________________________________________ __________________________________________________________ || Base Compare Obs || gr2 gr2 Diff. % Diff ________ || _________ _________ _________ _________ || 3 || 72.0000 73.0000 1.0000 1.3889 4 || 94.0000 74.0000 -20.0000 -21.2766 ________ || _________ _________ _________ _________ || N || 4 4 4 4 Mean || 86.2500 81.5000 -4.7500 -4.9719 Std || 9.9457 9.4692 10.1776 10.8895 Max || 94.0000 92.0000 1.0000 1.3889 Min || 72.0000 73.0000 -20.0000 -21.2766 StdErr || 4.9728 4.7346 5.0888 5.4447 t || 17.3442 17.2136 -0.9334 -0.9132 Prob>|t| || 0.0004 0.0004 0.4195 0.4285 || Ndif || 2 50.000% DifMeans || -5.507% -5.828% -4.7500 r, rsq || 0.451 0.204 __________________________________________________________

Note:    If you use a wide line size with PRINTALL, PROC COMPARE prints the value comparison result for character variables next to the result for numeric variables. In that case, PROC COMPARE calculates only NDIF for the character variables.  

Comparison Results for Observations (Using the TRANSPOSE Option)

 _OBS_1=number-1  _OBS_2=number-2

Partial Output shows the differences in PROCLIB.ONE and PROCLIB.TWO by observation instead of by variable.

Partial Output

Comparison Results for Observations _OBS_1=1 _OBS_2=1: Variable Base Value Compare Diff. % Diff gr1 85.0 84.00 -1.000000 -1.176471 _OBS_1=2 _OBS_2=2: Variable Base Value Compare state MD MA _OBS_1=3 _OBS_2=3: Variable Base Value Compare Diff. % Diff gr1 78.0 79.00 1.000000 1.282051 gr2 72.000000 73.000000 1.000000 1.388889 _OBS_1=4 _OBS_2=4: Variable Base Value Compare Diff. % Diff gr2 94.000000 74.000000 -20.000000 -21.276596 state MA MD

If you use an ID statement, the identifying label has the following form:

ID-1=ID-value-1 ... ID-n=ID-value-n

Note:   When you use the TRANSPOSE option, PROC COMPARE prints only the first 12 characters of the value.  

Output Data Set (OUT=)

By default, the OUT= data set contains an observation for each pair of matching observations. The OUT= data set contains the following variables from the data sets you are comparing:

• all variables named in the BY statement

• all variables named in the ID statement

• all matching variables or, if you use the VAR statement, all variables listed in the VAR statement.

In addition, the data set contains two variables created by PROC COMPARE to identify the source of the values for the matching variables: _TYPE_ and _OBS_.

_TYPE_

is a character variable of length 8. Its value indicates the source of the values for the matching (or VAR) variables in that observation. (For ID and BY variables, which are not compared, the values are the values from the original data sets.) _TYPE_ has the label Type of Observation. The four possible values of this variable are as follows:

BASE

The values in this observation are from an observation in the base data set. PROC COMPARE writes this type of observation to the OUT= data set when you specify the OUTBASE option.

COMPARE

The values in this observation are from an observation in the comparison data set. PROC COMPARE writes this type of observation to the OUT= data set when you specify the OUTCOMP option.

DIF

The values in this observation are the differences between the values in the base and comparison data sets. For character variables, PROC COMPARE uses a period (.) to represent equal characters and an X to represent unequal characters. PROC COMPARE writes this type of observation to the OUT= data set by default. However, if you request any other type of observation with the OUTBASE, OUTCOMP, or OUTPERCENT option, you must specify the OUTDIF option to generate observations of this type in the OUT= data set.

PERCENT

The values in this observation are the percent differences between the values in the base and comparison data sets. For character variables the values in observations of type PERCENT are the same as the values in observations of type DIF.

_OBS_

is a numeric variable containing a number further identifying the source of the OUT= observations.

For observations with _TYPE_ equal to BASE, _OBS_ is the number of the observation in the base data set from which the values of the VAR variables were copied. Similarly, for observations with _TYPE_ equal to COMPARE, _OBS_ is the number of the observation in the comparison data set from which the values of the VAR variables were copied.

For observations with _TYPE_ equal to DIF or PERCENT, _OBS_ is a sequence number that counts the matching observations in the BY group.

_OBS_ has the label Observation Number.

The COMPARE procedure takes variable names and attributes for the OUT= data set from the base data set except for the lengths of ID and VAR variables, for which it uses the longer length regardless of which data set that length is from. This behavior has two important repercussions:

• If you use the VAR and WITH statements, the names of the variables in the OUT= data set come from the VAR statement. Thus, observations with _TYPE_ equal to BASE contain the values of the VAR variables, while observations with _TYPE_ equal to COMPARE contain the values of the WITH variables.

• If you include a variable more than once in the VAR statement in order to compare it with more than one variable, PROC COMPARE can include only the first comparison in the OUT= data set because each variable must have a unique name. Other comparisons produce warning messages.

Output Statistics Data Set (OUTSTATS=)

When you use the OUTSTATS= option, PROC COMPARE calculates the same summary statistics as the ALLSTATS option for each pair of numeric variables compared (see Table of Summary Statistics ). The OUTSTATS= data set contains an observation for each summary statistic for each pair of variables. The data set also contains the BY variables used in the comparison and several variables created by PROC COMPARE:

_VAR_

is a character variable containing the name of the variable from the base data set for which the statistic in the observation was calculated.

_WITH_

is a character variable containing the name of the variable from the comparison data set for which the statistic in the observation was calculated. The _WITH_ variable is not included in the OUTSTATS= data set unless you use the WITH statement.

_TYPE_

is a character variable containing the name of the statistic contained in the observation. Values of the _TYPE_ variable are N, MEAN, STD, MIN, MAX, STDERR, T, PROBT, NDIF, DIFMEANS, and R, RSQ.

_BASE_

is a numeric variable containing the value of the statistic calculated from the values of the variable named by _VAR_ in the observations in the base data set with matching observations in the comparison data set.

_COMP_

is a numeric variable containing the value of the statistic calculated from the values of the variable named by the _VAR_ variable (or by the _WITH_ variable if you use the WITH statement) in the observations in the comparison data set with matching observations in the base data set.

_DIF_

is a numeric variable containing the value of the statistic calculated from the differences of the values of the variable named by the _VAR_ variable in the base data set and the matching variable (named by the _VAR_ or _WITH_ variable) in the comparison data set.

_PCTDIF_

is a numeric variable containing the value of the statistic calculated from the percent differences of the values of the variable named by the _VAR_ variable in the base data set and the matching variable (named by the _VAR_ or _WITH_ variable) in the comparison data set.

Note:   For both types of output data sets, PROC COMPARE assigns one of the following data set labels:

Comparison of base-SAS-data-set
with comparison-SAS-data-set

Comparison of variables in base-SAS-data-set

See Creating an Output Data Set of Statistics (OUTSTATS=) for an example of an OUTSTATS= data set.

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