In the categorical week of PHLT 8331, chi-square compares clinics and McNemar's test compares patients with themselves, each chosen for how its counts arose and reported with a difference in proportions. Searches like "phlt 8331 week 7 assignment example", "phlt8331 week 7 sample" and "phlt 8331 week 7 example" land here.
What a finished PHLT 8331 Week 7 categorical test looks like
Three pages built on two contingency tables and their test output. The first is a clinics-by-control table with row percentages, showing the share of patients controlled at each clinic. Its chi-square test of independence is reported with df and the exact p-value, and a sentence confirms that every expected count is comfortably large. Standardized residuals point to the clinic whose control rate departs most from the others. The second table cross-classifies the same patients' control status at enrollment and at six months. Only discordant patients, those who changed status, inform McNemar's test, a point made before it is reported. Each test is paired with an effect in proportions: the gap between the highest and lowest clinics, and the net change in the share controlled, each with a confidence interval.
How a PHLT 8331 Week 7 example is structured
The analysis is organized by how the counts arose, because that decides the test. Independent groups come first: each patient belongs to one clinic, so the clinic comparison uses a test of independence, and the write-up states that condition before any output. Expected counts are checked and reported. Standardized residuals then show where the difference lives. Paired counts come second: the same patients classified twice, so a test of independence would be wrong, and the analysis explains why McNemar's test draws only on patients who changed. Each section closes with an effect in proportions and its interval, since a p-value alone says nothing about size. A final paragraph separates the two findings for a reader: clinics differ in control, and control improved over time, and neither finding shows why.
Independent groups, one test
Each patient attends one clinic, so the three groups are independent and a chi-square test of independence fits. The write-up states that condition before the output, since it decides which test applies.
Expected counts, confirmed
The line SPSS prints about small expected counts is quoted and read: no cell falls short, so the approximation holds for this table. Leaving it out would give a reader no way to know the check happened.
Which clinic stands apart
Standardized residuals show one clinic with fewer patients controlled than independence would predict. Most of the overall result is attributed to that clinic, instead of implying all three differ.
Only the changers count
McNemar's test uses patients whose status changed between readings. Those controlled at both points, or neither, carry no information about change, and the section shows why a test ignoring the pairing would mislead.
Proportions with intervals
Each test is paired with an effect: the gap between clinics and the net change in the share controlled, each with a confidence interval. A reader learns how much, not only whether.
Where marks go in PHLT 8331 Week 7
Matching the test to how the counts were collected is the criterion this week is designed around. Applying a chi-square test of independence to the same patients measured twice ignores the pairing and costs the core line, however accurate the arithmetic. Graders check that the expected-count condition was examined and reported, not assumed. The residuals paragraph earns analytic credit by locating the difference; a write-up concluding that all clinics differ from a significant overall test has overread it. McNemar's logic is expected in a sentence, and reports showing that the author understands why concordant pairs drop out score higher. Effect sizes in proportions with intervals are required in most sections. Interpretation is marked on restraint about causes, and formatting of the tables takes the smallest share.
Get a PHLT 8331 Week 7 example written to your instructions
Post the Week 7 prompt and rubric to the desk, describing the categorical variables and how they were collected, grouped or paired. An analysis choosing its tests by that structure, with effects in proportions, arrives in 24-48h, and the opening request is free. Its counts are composite and exist only to carry the reasoning.
PHLT 8331 Week 7 questions, answered
When should Fisher's exact test replace chi-square?
When expected counts are small enough that the chi-square approximation becomes unreliable, which the output's footnote flags. Fisher's test computes the probability directly and does not rely on large-sample behavior, which is why it suits sparse tables. With well-populated cells, as in this registry, the two agree closely. Whichever applies, the analysis reports the check and the test used.
Why does McNemar's test ignore patients whose status did not change?
Because they carry no information about whether control became more or less common. A patient controlled at both times, or at neither, is the same before and after. The question is whether more patients moved into control than out of it, and only the patients who moved can answer that. The write-up states this in a sentence so no reader suspects data were discarded.
Is a difference in proportions better than an odds ratio here?
For a clinic audience, often yes, because a difference in percentage points is easier to act on. Odds ratios are standard in some analyses and appear in later courses, but they are frequently misread as risk ratios. The write-up can report both if the prompt asks, with a plain sentence for whichever one the audience will use.