Researchers were interested in examining the impact poverty may have on self-perceptions of health. Participants were asked to rate their health as in good or poor. Their income level was categorized as above or below the poverty line. Use the two tables below to answer the following questions.
Chi-Square Tests |
|||||
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
4.894a |
1 |
.027 |
||
Continuity Correctionb |
4.208 |
1 |
.040 |
||
Likelihood Ratio |
5.595 |
1 |
.018 |
||
Fisher's Exact Test |
.025 |
.016 |
|||
Linear-by-Linear Association |
4.888 |
1 |
.027 |
||
N of Valid Cases |
860 |
Risk Estimate
Value |
95% Confidence Interval |
||
Lower |
Upper |
||
Odds Ratio for Poor health self-rating (Not in poor health / In poor health) |
.412 |
.183 |
.926 |
For cohort Poverty status = Below poverty |
.844 |
.755 |
.943 |
For cohort Poverty status = Above poverty |
2.048 |
1.017 |
4.127 |
N of Valid Cases |
860 |
1) In the above study the
Null hypothesis- H0: There is no impact if poverty on self-rated health
Alternate hypothesis- H1: Poverty may have a negative impact on health
2)
Pearson Chi-Square= 4.894(1)
which is calculated from the Pearson Chi-Square test and p-value is given as
P-VALUE =.027 < 0.05 (level of significance )
therefore at 5% we reject the null hypothesis.
3) In the term of the original research hypothesis, the odds ratio can be interpreted as
the odd of poor self-rated health is higher among poor than that of the non-poor
4) Odds Ratio for Poor health self-rating (Not in poor health / In poor health)= .412
which means that-
percentage = (1- 0.412) *100%= 58.8%
Now it can be interpreted easily as
The odds of poor self-rated health is 58% lower among the non-poor than to the poor.
3)
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