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Adverse Reactions 3
Test whether adverse reaction times differ significantly based on the gender of patients. |
Physician Referrals 3: Problem |
A study was done to investigate the effect of hospice marketing visits on the change in number of referrals received from doctors. There were two types of visits (one accompanied by a physician, and one by the hospice staff only), and the change in referrals after one month (change1) and after three months (change3) were recorded, along with other variables.
Use the Kruskal-Wallis test to determine whether the change in referrals after three months differs for the two types of visits. |
SAS Institute Inc.
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Physician Referrals 3: Sample Data | |
The Hospice data set contains data about referrals received from physicians after a visit by a hospice marketing nurse. These are the variables in the data set: Name | Type | Description | | ID | num | physician ID | | Practice | char | type of practice | | Date | char | date of visit | | Change3 | num | change in number of referrals after 3 months | | Change1 | num | change in number of referrals after one month | | Visit | char | type of visit | |
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Source of Data
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This data is sample data from SAS Institute Inc.(database delimiter) |
Physician Referrals 3: Solution |
You’re testing the following hypotheses:
Ho: no difference in change in referrals after
three months between the two types of visits
versus the two-sided alternative
Ha: there is a difference in change in referrals after
three months between the two types of visits
The Kruskal-Wallis test statistic is K = 1.5991, with a one-sided p-value of 0. 2060. The p-value for our two-sided test is 2(0.2060) = 0.4120. This fails to give sufficient evidence against the null hypothesis, so we cannot conclude that there is a difference in the change in referrals after three months between the two types of visits. |
Adverse Reactions 3: Problem |
The manufacturers of a medication were concerned about adverse reactions in patients that were treated with their drug. Data on adverse reactions was gathered and stored in a file. The duration of the adverse reaction was recorded as the dependent variable.
Patients were either given a placebo or received the standard drug regimen. Test whether there is a difference in adverse reaction times between males and females using the two sample Kruskal-Wallis test. Use a significance level of α = 0.05. ~nl~ |
Lee Creighton (modified by Paris Faison)
SAS Institute Inc.
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Adverse Reactions 3: Sample Data | |
The Adverser data set contains information on patients and their adverse reactions to a drug treatment. These are the variables in the data set: Name | Type | Description | | PATIENT_ID | num | patient identification number | | TREATMENT_GROUP | char | treatment patient received (placebo or standard drug) | | TOTAL_DAILY_DOSE | num | daily dosage | | DAY_ON_DRUG | num | number of days patient was on treatment | | AGE | num | age | | SEX | char | sex | | WEIGHT | num | weight | | ADVERSE_REACTION | char | type of adverse reaction | | RACE | char | race | | ADR_SEVERITY | char | level of severity of adverse reaction | | RELATION_TO_DRUG | char | relation of adverse reaction to drug | | ADR_DURATION | char | duration of adverse reaction | |
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Source of Data
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Sall, J., Creighton, L., & Lehman, A. (2006). JMP Start Statistics, Third Edition. Cary, NC: SAS Institute Inc. |
Adverse Reactions 3: Solution |
The results of the Kruskal-Wallis test generated by the NPAR1WAY procedure in SAS shows a p-value of 0.6356. This outcome is not significant at the α = 0.05 level. So we can conclude that the data does not provide evidence to suggest that there is a difference in adverse reaction times between males and females. |
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