| Software Output Example Raw
data from1993 survey of U.S. adults
Crosstabulation:
GUNLAW (Rows) by
SEX (Columns)
Column
Variable Label: Respondent's Sex
Row
Variable Label: Gun permits
Count |
Row % |
Col % |
Total % | Male |
Female | Total
--------------------------------------------
Favor | 314| 497| 811
| 38.72| 61.28|
| 73.88| 88.91|
82.42
| 31.91| 50.51|
--------------------------------------------
Oppose | 111| 62| 173
| 64.16| 35.84|
| 26.12| 11.09|
17.58
| 11.28| 6.30|
--------------------------------------------
| 425| 559| 984
Total | 43.19|
56.81| 100.00
Chi-square
Value
DF p
<
-----------------------------------------------------------
Pearson
37.622
1 0.0000 A
Likelihood
Ratio
37.417 1 0.0000
Yate's
Correction
36.592 1 0.0000 B
Measures
of Association
-------------------------------------
Cramer's
V
.196
C
Pearson
C
.192
Lambda
Symmetric
.082 D
Lambda
Dependent=Row
.000
Lambda
Dependent=Column
.115
E
Note:
00.00% of the cells have an expected frequency <5
A Statistically significant (most common measure used
for significance)
B When sample sizes are small, the continuous
chi-square value tends to be too large. The
Yates continuity correction adjusts for this bias in 2x2 contingency tables. Regardless of
sample size, it is a preferred measure for chi-square tests on 2x2 tables.
C Weak association (both Cramer’s V and Pearson
C)
D A symmetric lambda is used when identification of
independent and dependent variables is not useful
E Knowing a person’s sex can reduce prediction
error by 11.5%.
|
