Using n25;inc=
Suppose that instead of using factors of +2 to -2, you are asked to use factors of 5 to 1, where 5 indicates that the respondent agrees very much and 1 means that they disagreed very much. Since these match the way the responses have been coded, you can use an n25 with an inc= to define the factors:
l vers3
col 210;Agrees Very Much=5;Agrees Somewhat=4;
+Neither Agrees Nor Disagrees=3;Disagrees Somewhat=2;
+Disagrees Very Much=1;Refused='&'
n25;inc=c210;c=c210'1/5'
n12Mean;dec=2
This example excludes respondents refusing to answer by adding a condition on the n25, indicating that it refers only to those respondents having a 1, 2, 3, 4 or 5 code in c210. If you keep the same number of respondents in each group as before, the mean will be 2.30 as shown below:
Mean = [(5´25)+(4´19)+(3´7)+(2´15)+(1´3)] / 69
When you have missing values processing switched on in the tab section, Quantum automatically excludes records with the value missing_ from the inc= element. In the axis:
l rental
val c(156,157);Base;i;None=0;1-5;6-10;11-15;16-20;21-30;31+
n01DK/NA;c=-
n25;inc=c(156,157)
n12Mean number of videos rented by all who rent videos;dec=2
the n25 statement includes any respondent for whom c(156,157) contain a numeric value. Respondents for whom the field is non-numeric or totally blank are excluded. To create the same axis without using missing values processing, write:
n25;inc=c(156,157);c=c(156,157).in.(1:99,$00$)
Note If you want other values to be treated the same as missing values, add the option
missing=logical_expression to the
n25 statement. For more information, see the
inc= in
Data options.
See also