PHLT 8064 Week 3 Design Comparison Paper Example

Course	PHLT 8064 Dissertation Seminar III
Week	Week 3
Paper type	Design comparison paper
Length	About 790 words, 5 pages
Format	APA 7 student paper
School	Walden University
Program	PhD in Public Health
Updated	October 2026

Free sample paper for PHLT 8064 Week 3

Two Ways to Answer One Question: A Prospective Family Cohort and a Retrospective Registry Cohort Weighed Against the Same Research Question on Drive Time and Diagnostic Hearing Evaluation

Student Name

Walden University

PHLT 8064: Dissertation Seminar III

Instructor Name

Month Day, Year

What this page is doingThe title holds both designs to one question, which is the only fair basis for choosing between them.

Two Ways to Answer One Question: A Prospective Family Cohort and a Retrospective Registry Cohort Weighed Against the Same Research Question on Drive Time and Diagnostic Hearing Evaluation

The Question Both Designs Must Answer

For babies referred from newborn hearing screening in the composite state, do those with a longer drive to the closest pediatric audiology clinic have lower odds of a recorded diagnostic evaluation within three months of birth? Each design below is judged on how well it answers that sentence, not a neighboring question it might answer better.

What this page is doingRestating the question once, before either design appears, prevents the comparison from drifting toward whichever design is more interesting.

The Two Candidates

A prospective cohort would enroll families when an infant does not pass screening at the birth hospital, survey parents about travel, work schedules and car access, and follow each infant to three months to see whether an evaluation occurs. A retrospective cohort would take every infant referred from screening across several birth years from the program's registry, link each record to the birth certificate for address and covariates, and observe documented evaluations that have already happened. Both are cohort designs in the sense Grimes and Schulz (2002) describe, moving from exposure toward outcome; they differ in when the observation takes place and who supplies the data.

Table 1

The Two Designs Compared on the Same Question

Feature	Prospective family cohort	Retrospective registry cohort \|
What it could estimate	Association of drive time with evaluation, plus parent-reported reasons	Association of drive time with documented evaluation across all referred infants \|
Exposure measurement	Address reported by parents at enrollment	Geocoded address from the birth certificate \|
Outcome measurement	Evaluation confirmed by follow-up call and program records	Evaluation as reported to the registry \|
Infants it would miss	Families who decline enrollment or cannot be reached	Evaluations done out of state or never reported \|
Main bias	Selection: agreeing families may be those who keep appointments	Misclassification: unreported evaluations look like missed ones \|
Time to an answer	About two years of enrollment plus follow-up	Months, once access is approved \|
Access needed	Hospital partners, consent, survey staff	Data use agreement and vital records approval \|

Note. Time estimates assume roughly 350 referred infants a year in the composite state.

Where Each Design Breaks

The prospective cohort's weakness sits at its front door. Families must agree to a survey within days of a stressful screening result, and the families who agree are plausibly the ones most organized, most worried and most likely to attend an appointment anyway. Galea and Tracy (2007) document how participation in epidemiologic studies has declined and how nonparticipants can differ from participants in ways tied to the outcome. If the families least likely to follow up are also least likely to enroll, the study would underestimate how often evaluations are missed and could flatten any difference by distance.

The retrospective cohort's weakness sits at its back door. The registry knows only what audiologists report. An infant evaluated across the state line, or at a clinic that never sent the result, appears identical to an infant who was never seen. Mason et al. (2008) describe how inconsistent documentation makes follow-up figures hard to compare across programs. If families far from in-state sites are more likely to use out-of-state clinics, this misclassification would make distant infants look worse than they are.

What this page is doingNaming each design's characteristic bias, and the direction it would push the result, is what makes the comparison more than a list of pros and cons.

A Third Option, Folded

A case-control study could sample infants without a documented evaluation and compare their drive times with a sample of infants who were evaluated. Case-control designs earn their place when outcomes are rare or when measuring exposure is expensive (Schulz & Grimes, 2002). Neither condition holds here. Missing evaluations are common, and drive time can be computed for every infant at almost no extra cost once addresses are geocoded. Sampling from a registry that already holds every referred infant would discard information and add sampling error, so the option is set aside.

The Decision

The retrospective registry cohort is chosen. It answers the question as written, for every referred infant, within the time a dissertation allows, and its main bias can be examined directly with a sensitivity analysis that treats ambiguous statuses as unknown rather than as missed. The choice is not free. Three things the prospective design would have given are lost:

What Records Cannot Give

First, reasons. Parents could have said why an appointment was missed, and the registry cannot. Second, exposure in the family's own terms. A survey could have asked about car access and work flexibility, which may matter as much as minutes on a map. Third, the current address. Parents enrolled at birth could report a move, while the birth certificate fixes the address on the day of delivery. Each loss will be stated in the limitations, and the first points toward a follow-up study the dissertation's findings could help design.

References

Galea, S., & Tracy, M. (2007). Participation rates in epidemiologic studies. Annals of Epidemiology, 17(9), 643-653. https://doi.org/10.1016/j.annepidem.2007.03.013

Grimes, D. A., & Schulz, K. F. (2002). Cohort studies: Marching towards outcomes. The Lancet, 359(9303), 341-345. https://doi.org/10.1016/S0140-6736(02)07500-1

Mason, C. A., Gaffney, M., Green, D. R., & Grosse, S. D. (2008). Measures of follow-up in early hearing detection and intervention programs: A need for standardization. American Journal of Audiology, 17(1), 60-67. https://doi.org/10.1044/1059-0889(2008/007)

Schulz, K. F., & Grimes, D. A. (2002). Case-control studies: Research in reverse. The Lancet, 359(9304), 431-434. https://doi.org/10.1016/S0140-6736(02)07605-5

PHLT 8064 Week 3 instructions, in plain terms

The third assignment typically calls for a comparison of at least two plausible designs for the dissertation question, ending in a justified choice. Faculty want the question restated so both designs are judged against the same standard, and they expect a structured comparison, often a table, covering measurement, sampling, bias, timeline and access. Each design's characteristic threat to validity should be named along with the direction it would push results. Candidates are encouraged to address a third design that a committee member might raise, even briefly. The decision should name what is lost as well as gained, since every choice gives something up. A paper of three to five pages is the norm, and each claim about strengths and weaknesses should rest on a methodological source such as an epidemiology text or design primer.

How this PHLT 8064 Week 3 example is built

The sample opens by quoting the research question and promising to judge both designs only by how well they answer it. A section describes the prospective option, enrolling families after a failed screen and surveying them, and the retrospective option, linking every registry referral to birth certificates, then cites a cohort primer to place both in the same family of designs. Table 1 compares them on seven features, and the row listing which infants each design would miss carries the argument. A section on where each design breaks traces selection bias at the front door and misclassification at the back door, with the direction each would bias the estimate. A case-control alternative is set aside because outcomes are common and exposure is cheap to measure. The decision and its three losses close the paper.

Where the marks sit in the PHLT 8064 Week 3 rubric

Graders in this seminar want the decision to grow out of the comparison, not to be fixed in advance and decorated with a table. The sample earns that credit by holding both designs to one question and by naming the bias each would introduce, including which way it would push the result. Accuracy about design terms is checked: calling the registry study a case-control study, or treating any prospective design as automatically stronger, would cost marks. Addressing a third option shows anticipation of committee questions and is rewarded where rubrics include critical thinking. Naming the losses of the chosen design matters as much as its gains. Rows for scholarly support and APA style reward citing design sources correctly, and concise prose helps the paper score on organization.

PHLT 8064 Week 3 help: mistakes that cost marks

Design comparisons go wrong when the author already prefers one option and builds a lopsided table to justify it. Every advantage of the favored design appears, every weakness of the other. Instructors spot this quickly, especially when the chosen design's own bias is never named. Another mistake is comparing designs in general instead of for this question, so a paragraph on the strengths of randomized trials appears in a registry dissertation where randomization is impossible. Some students also forget the practical rows, approvals and time, which often decide the matter in a doctoral timeline. Write the losses section first if it helps; it forces honesty about what the chosen design cannot do. We can write a comparison built around your own question and the designs your committee has suggested.

Get a PHLT 8064 Week 3 example written to your instructions

Name the question and the two designs your section wants weighed, with the comparison prompt for Week 3 and its rubric. A symmetrical table follows, rows chosen for your question, a note on any obvious third option, and a decision listing what the losing design would have given. No fee on a first request, back in 24 to 48 hours; the registry is illustrative.

More PHLT 8064 papers and PhD in Public Health samples

PHLT 8064 Week 3 questions, answered

Is a prospective design always stronger than a retrospective one?

No. Prospective designs control measurement and timing, but they depend on people agreeing to take part, and that agreement can bias results. The example's retrospective cohort covers every referred infant, including families who would never answer a survey. Which is stronger depends on which bias matters more for the question. Your comparison should argue that for your topic rather than rely on a ranking.

Why mention a design that is rejected in one paragraph?

Because a committee member may raise it, and a written answer is stronger than a spoken one improvised at the defense. The example addresses a case-control study within the registry and explains that sampling from a fully available cohort loses information without saving effort. A brief, reasoned dismissal shows you considered the option. A long one can distract from the two designs that actually compete.

Where can I find a free PHLT 8064 Week 3 sample paper?

You are on it: the full Week 3 design comparison is published here, weighing a family survey cohort against a registry cohort for one question on infant hearing follow-up. The comparison table, bias analysis and decision are all included, with margin notes on how each part scores.

What is the difference between selection bias and misclassification?

Selection bias arises when the people who end up in a study differ from the target population in ways linked to the outcome, as when only organized families enroll. Misclassification happens when someone lands in the wrong group; an infant evaluated out of state but logged as never evaluated is one example.

Do I need a table to compare designs?

A table is not required everywhere, but it is the clearest way to show that both designs were judged on the same features. The sample's table has seven rows; aim for the features on which your options truly differ and skip rows where they are identical.