| Course | HLTH 8560E Advanced Analysis of Secondary Data |
|---|---|
| Week | Week 3 |
| Paper type | Codebook review |
| Length | About 620 words, 5 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | PhD in Public Health |
| Updated | October 2026 |
Free sample paper for HLTH 8560E Week 3
Codebook Review: Testing What the NHANES 2011-2018 Documentation Claims About Each Item a Depressive Symptom and Glycohemoglobin Analysis Will Use, and Logging Where It Goes Silent
Student Name
Walden University
HLTH 8560E: Advanced Analysis of Secondary Data
Instructor Name
Month Day, Year
Codebook Review: Testing What the NHANES 2011-2018 Documentation Claims About Each Item a Depressive Symptom and Glycohemoglobin Analysis Will Use, and Logging Where It Goes Silent
Scope and Method
This review covers the four NHANES cycles from 2011-2012 to 2017-2018 chosen last week. For every item the analysis will use, I recorded the universe (who was asked), the reference period, the codes, any change across cycles, and anything the documentation does not say. Silences are logged as findings because each one becomes an analytic decision later (Johnson et al., 2013).
Item-by-Item Record
Table 1
Universe, Period, Codes and Silences for Each Item
| Item | Universe and period | Codes | What the documentation does not settle | |
|---|---|---|---|
| DIQ010 diagnosed diabetes | All ages; ever told, other than during pregnancy | 1 yes, 2 no, 3 borderline, 7 refused, 9 don't know | How borderline answers should be treated | |
| DIQ050 insulin now | Current use | 1 yes, 2 no, 7, 9 | Nothing on dose or type; routing must be read in the questionnaire | |
| LBXGH glycohemoglobin | Examined participants aged 12 and older; reflects recent months | Percent, continuous | No analytic cut points; method notes differ by cycle | |
| DPQ010 to DPQ090 PHQ-9 items | Adults 18 and older in the examination center; past two weeks | 0 to 3, 7 refused, 9 don't know | No total score and no rule for partial answers | |
| RIDAGEYR age | All participants | Years | Values of 80 mean 80 and older | |
| INDFMPIR income to poverty | All participants | Ratio | Values of 5 mean 5 or more; missing when income unreported | |
| WTMEC2YR, SDMVSTRA, SDMVPSU | All participants | Weight; masked stratum and unit | Zero weight for those interviewed but not examined | |
Entries reflect the 2011-2018 data documentation and questionnaires; DIQ050 routing is checked against each cycle's instrument before use.
Findings From the Review
The first finding concerns borderline diabetes. Among adults aged 20 and older across the four cycles, 594 answered DIQ010 with code 3, and 15 refused or did not know. The documentation lists the code but gives no advice on whether borderline means prediabetes, a passing high reading, or something else. I will exclude these respondents from the diabetes group and say so, since the question concerns people who were told they have diabetes.
The second concerns the PHQ-9. The file releases nine item scores and leaves totaling to the analyst. Kroenke et al. (2001) score the instrument from 0 to 27, with 10 or more marking at least moderate symptoms, but they do not address an interview in which one item was refused. Among examined adults with diagnosed diabetes and a glycohemoglobin value, 25 had a refused or don't-know answer on at least one item, and 223 had no depression screener record at all. The codebook says nothing about why records are absent.
The third concerns weights. Because the PHQ-9 and the blood sample both come from the examination center, the examination weight applies, and it is zero for participants who completed only the household interview (Chen et al., 2020). Using the interview weight would quietly include people with no outcome measured.
The fourth concerns age. Nearly one in ten adults in the eventual analytic group carries the top-coded value of 80, so any age band above 80 cannot be built from this release.
The last concerns race and ethnicity. The three-category recode used before 2011 was supplemented in 2011-2012 by a version that separates non-Hispanic Asian adults. Pooling within 2011-2018 lets me use the newer variable consistently.
What the Review Changes
Three decisions follow directly: borderline answers are excluded, partial PHQ-9 records are not prorated in the main analysis, and only examination weights are used. Each will appear in the variable map and in the methods section with this review cited as its source.
References
Chen, T. C., Clark, J., Riddles, M. K., Mohadjer, L. K., & Fakhouri, T. H. I. (2020). National Health and Nutrition Examination Survey, 2015-2018: Sample design and estimation procedures (Vital and Health Statistics, Series 2, No. 184). National Center for Health Statistics.
Johnson, C. L., Paulose-Ram, R., Ogden, C. L., Carroll, M. D., Kruszon-Moran, D., Dohrmann, S. M., & Curtin, L. R. (2013). National Health and Nutrition Examination Survey: Analytic guidelines, 1999-2010 (Vital and Health Statistics, Series 2, No. 161). National Center for Health Statistics.
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606-613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x
What the HLTH 8560E Week 3 instructions ask for
Students review the documentation for every variable their analysis will use before working with the data. The review should record who was asked each item, the period it refers to, how answers are coded, whether anything changed across survey cycles and what the documentation leaves unsaid. Faculty treat gaps in the documentation as findings, because each one turns into a decision the analyst must make and report. Design variables and weights belong in the review alongside content items. Most sections expect a table plus short written findings, and the strongest reviews test documentation against the file itself, reporting counts where the codebook is silent. A closing statement of the decisions the review forces helps link this week to the variable map that follows.
How this HLTH 8560E Week 3 example is built
An opening section sets the scope, four cycles from 2011 to 2018, and defines a silence as a finding, citing the NHANES analytic guidelines by Johnson and colleagues. Table 1 gives one row per item with columns for universe and period, codes and what the documentation does not settle. Five findings follow in prose. The first reports the 594 borderline answers and the 15 refusals. The second explains that PHQ-9 totals are left to the analyst, cites Kroenke and colleagues for the scoring, and counts 25 partial records and 223 missing ones. The third explains the examination weight with Chen and colleagues cited. The fourth notes the age cap, and the fifth the newer race and ethnicity variable. A short section lists the three resulting decisions.
Reading the HLTH 8560E Week 3 rubric
Faculty grade the review on whether it was done against the file. A summary of the codebook, however tidy, earns limited credit because it cannot show anything the documentation does not already say. Higher marks go to reviews that report where the documentation is silent and back that with counts from the data, such as how many respondents chose a borderline code. Accuracy about universes, reference periods and codes is checked item by item, and an error in a weight or skip pattern is treated as serious because it would corrupt every later estimate. Including the design variables shows awareness that NHANES is not a simple sample. The final section earns its share when each finding ends in a decision the analysis will carry forward.
Common HLTH 8560E Week 3 mistakes, and how to avoid them
Codebook reviews frequently copy variable labels and value lists into a table and stop. That records the documentation without testing it. To write a stronger review, start from your variable list and, for each item, find the questionnaire screen that produced it, so you know who was routed to it. Note the reference period in the exact words used. Then run simple frequencies and compare them with the codebook: look for codes it does not mention, refusals stored as numbers and records missing without explanation. Record every gap as a finding with its count. Check the weights and design variables too, because choosing the wrong weight changes every estimate. Finish by listing the decisions each finding forces. We can build a codebook review for the exact items in your own analysis.
Get a HLTH 8560E Week 3 example written to your instructions
Share the Week 3 instructions and rubric along with the dataset and items your analysis will use. A review table with universes, reference periods and a findings section is ready inside 24-48h, and there is no fee on a first request. Its items come from a composite reading of one public file, so the silences in your documentation still need finding by you.
More HLTH 8560E papers and PhD in Public Health samples
- HLTH 8560E Week 1: Dataset Orientation Post
- HLTH 8560E Week 2: Dataset Selection Memo
- HLTH 8560E Week 4: Survey Round Discussion Post
- HLTH 8560E Week 5: Analytic Variable Map
- HLTH 8560E Week 6: Analytic Sample Derivation
- HLTH 8560E Week 7: Survey Analysis Plan
- HLTH 8560E Week 8: Weighted Results Section
- HLTH 8560E Week 9: Recode Peer Replies
- HLTH 8560E Week 10: Data Constraints Memo
- HLTH 8560E Week 11: Journal Manuscript Draft
- HLTH 8551 Week 3: Topic Narrowing Memo
- HLTH 8475 Week 3: Implementation Logic Model
- HLTH 8402 Week 3: Disaggregated Population Profile
- HLTH 8392 Week 3: Burnout Framing Critique
HLTH 8560E Week 3 questions, answered
Is a codebook review the same as a data dictionary?
No. A data dictionary lists what each variable is; a review tests whether the documentation tells an analyst enough to use it correctly. The review adds judgment: whether the universe is stated, whether the reference period fits the question, whether an item changed between releases. Many sections expect both, with the dictionary in an appendix and the review as the main text.
What if the documentation contradicts the data file?
Report both and say which one the analysis will follow, with a reason. A frequency showing codes the codebook never mentions, or a universe wider than the stated one, is a real finding. Contacting the data provider is sometimes possible, and noting the query in the review is better than resolving the conflict silently in your own favor.
How many items should the review cover?
Every item the analysis will touch, including design variables and weights, and nothing beyond that. For a single-question project this is usually a few dozen rows at most. Reviewing the whole codebook spends words on items that play no role, while skipping covariates leaves the review blind to the variables most likely to hide a skip pattern.
Where can I find a free HLTH 8560E Week 3 sample paper?
The full Week 3 codebook review is shown on this page, testing the NHANES 2011-2018 documentation for each item in a depressive symptom and glycohemoglobin analysis, with real counts for each silence and three references.
Why use the examination weight instead of the interview weight?
Both the PHQ-9 and the blood sample come from the examination visit, and the examination weight is zero for people who completed only the household interview. Using the interview weight would count adults who have no outcome measured.