| Course | PUBH 9102 Completing Doctoral Capstone II |
|---|---|
| Week | Week 5 |
| Paper type | Non-response note |
| Length | About 670 words, 5 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | PhD in Public Health |
| Updated | October 2026 |
Free sample paper for PUBH 9102 Week 5
What the Roster and the Permit File Can Say About Those Who Are Missing: A Non-Response Note for a Composite County Pool Inspection Capstone
Student Name
Walden University
PUBH 9102: Completing Doctoral Capstone II
Instructor Name
Month Day, Year
What the Roster and the Permit File Can Say About Those Who Are Missing: A Non-Response Note for a Composite County Pool Inspection Capstone
Scope of the Note
Two groups are missing from the analysis of pools in Alder County, the invented setting of this study: three inspectors who declined an interview, and 119 facilities that left the permit population before the analytic set. This note compares each absent group with those who took part, using only fields the division already holds, and then sets out how their absence could tilt the findings. It does not say which way the findings were actually tilted, because nothing available can answer that.
Inspectors Who Declined
Table 1
Interviewed and declining inspectors on roster fields
| Roster field | Interviewed (n = 6) | Declined (n = 3) | |
|---|---|---|
| Central District | 3 | 0 | |
| North District | 2 | 1 | |
| East District | 1 | 2 | |
| Under 5 years of service | 2 | 0 | |
| 5 to 14 years | 3 | 1 | |
| 15 years or more | 1 | 2 | |
| Inspected pools under the fixed schedule | 4 | 3 | |
Service bands are used because exact years could identify individuals in a group this small.
East District accounts for two of the three refusals, and two of those three people have served fifteen years or longer. All three inspected under the fixed schedule before the switch. The roster cannot say why they declined. East reset its field schedule during the interview period, which is a plausible reason, but plausible is not recorded, and I have not asked, since asking would press people who have already said no. Low response produces bias only where the reasons people stay out are tied to the outcome itself, and a response rate by itself cannot show whether they are (Groves, 2006).
Facilities That Fell Out
Table 2
Analytic set and excluded facilities on permit file fields
| Permit field | Analytic set (n = 319) | Excluded (n = 119) | |
|---|---|---|
| Higher tier at first record | 34% | 22% | |
| Middle tier at first record | 38% | 29% | |
| Lower tier at first record | 28% | 49% | |
| Any critical violation in first season on file | 41% | 36% | |
| Spa or splash pad | 31% | 52% | |
Excluded facilities include temporary permits, closures, changes of operator, tier changes and those with too few routine visits; tier is the tier at the facility's first record in the window.
Excluded facilities were more often lower tier and more often spas or splash pads. Their share with a critical violation in their first season was close to that of the analytic set. The difference in tier is partly built in, since lower-tier facilities were inspected less often after the switch and so more often fell short of two routine visits.
Possible Tilts, Not Tested
Three directions are possible. First, if long-serving East inspectors hold views on tier scheduling that differ from those interviewed, the themes on how schedules are set in practice may reflect newer staff and two districts more than the division as a whole. Second, if lower-tier facilities that dropped out had worse records than those that stayed, the post-switch repeat share in the lower tier would be understated, since the facilities left are the ones inspected often enough to remain. Third, closures may concentrate among facilities with chronic problems, which would remove high repeat risk from both periods unevenly. Each could be checked only with data not available: interviews with the three who declined, or inspection records for closed facilities from another source. Reporting guidance for observational work asks authors to describe nonparticipation and its possible effects without overstating them (Vandenbroucke et al., 2007).
What Changes in the Write-Up
The limitations section will name East District and long service as gaps in the interview strand. The results chapter will report lower-tier findings with a note on selection by visit frequency, and the sensitivity analysis will repeat the lower-tier model allowing one routine visit in a period, a check whose limits the interrupted time series literature already describes for short series (Lopez Bernal et al., 2017).
References
Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly, 70(5), 646-675. https://doi.org/10.1093/poq/nfl033
Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46(1), 348-355. https://doi.org/10.1093/ije/dyw098
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. PLoS Medicine, 4(10), Article e297. https://doi.org/10.1371/journal.pmed.0040297
Reading the PUBH 9102 Week 5 instructions
Non-response notes ask candidates to examine who did not take part in the study and what their absence might mean. Instructions commonly ask for a comparison of participants and non-participants on whatever information is available, a discussion of possible bias and a statement of how the findings will be qualified. Some prompts ask candidates to address both people who declined and units lost from records. Faculty want the analysis kept within the data the candidate is allowed to use, so notes that speculate about motives or invent characteristics for those missing usually lose credit, while those that compare carefully and label uncertainty earn it.
Inside the PUBH 9102 Week 5 example
An opening paragraph defines the two absent groups and promises not to claim any direction of bias. A table compares six interviewed and three declining inspectors on district, service band and experience of the fixed schedule, followed by a paragraph that names the East pattern and states that the roster cannot explain it. A second table compares the analytic set with excluded facilities on tier, venue type and first-season violations. Three possible tilts are set out in turn, each with the data that would be needed to check it. A last section says how the limitations, the lower-tier results and a sensitivity analysis will change because of the note. Service is reported in bands throughout to protect a small group.
PUBH 9102 Week 5 rubric: what earns full marks
Faculty generally read a non-response note for the line between what is known and what is not, and keeping that line visible earns most of the marks. Comparing responders and non-responders on recorded fields secures the core share, because it replaces speculation with data already held. Restraint over the East District pattern is credited heavily. Parallel treatment of excluded facilities earns a further portion, since attrition in records is often ignored. The Groves source supports the point that response rates alone do not reveal bias. Possible tilts paired with the evidence needed to test them show rigor. Committing to concrete changes in the write-up, rather than a general caution, often lifts a note into the top band.
PUBH 9102 Week 5 help: mistakes that cost marks
List everyone and everything that could have been in your study but is not. For each group, find the fields you already hold for both participants and non-participants, and compare them in a simple table. Describe any pattern you see, then stop: do not explain it unless you have evidence. Write out how the absence could push your findings each way, and what data would settle it. Finally, say what you will change in your limitations or analysis. If you are unsure which comparisons your data allow, we can write a sample note from your roster and records. Keep service years or ages in bands when groups are small, so no one can be recognized. Remember that a note like this protects your conclusions as much as it limits them.
Get a PUBH 9102 Week 5 example written to your instructions
Tell the desk who was eligible but never took part, what your records say about them and what they do not, plus the Week 5 prompt and rubric. Responders and non-responders are compared on recorded fields, and possible tilts are listed as hypotheses with tests. The first note comes free within 24 to 48 hours; every roster cell here is illustrative.
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PUBH 9102 Week 5 questions, answered
Where can I find a free PUBH 9102 Week 5 sample paper?
The full Week 5 non-response note is above, comparing absent inspectors and facilities in a composite pool inspection study.
Can I guess why people declined?
No. This example names the pattern and says the records cannot explain it.
What data can a non-response note use?
Only fields already held for both groups, here the roster and the permit file.
Does the note say how bias changed the results?
It lists possible directions and what would test them, without claiming which occurred.
Should excluded records be covered as well as people?
Yes. Facilities lost from the records receive a parallel comparison here.