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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using Person Fit Statistics to Detect Outliers in Survey Research
|
|---|---|
| Published in |
Frontiers in Psychology, May 2017
|
| DOI | 10.3389/fpsyg.2017.00863 |
| Pubmed ID | |
| Authors |
John M. Felt, Ruben Castaneda, Jitske Tiemensma, Sarah Depaoli |
| Abstract |
Context: When working with health-related questionnaires, outlier detection is important. However, traditional methods of outlier detection (e.g., boxplots) can miss participants with "atypical" responses to the questions that otherwise have similar total (subscale) scores. In addition to detecting outliers, it can be of clinical importance to determine the reason for the outlier status or "atypical" response. Objective: The aim of the current study was to illustrate how to derive person fit statistics for outlier detection through a statistical method examining person fit with a health-based questionnaire. Design and Participants: Patients treated for Cushing's syndrome (n = 394) were recruited from the Cushing's Support and Research Foundation's (CSRF) listserv and Facebook page. Main Outcome Measure: Patients were directed to an online survey containing the CushingQoL (English version). A two-dimensional graded response model was estimated, and person fit statistics were generated using the Zh statistic. Results: Conventional outlier detections methods revealed no outliers reflecting extreme scores on the subscales of the CushingQoL. However, person fit statistics identified 18 patients with "atypical" response patterns, which would have been otherwise missed (Zh > |±2.00|). Conclusion: While the conventional methods of outlier detection indicated no outliers, person fit statistics identified several patients with "atypical" response patterns who otherwise appeared average. Person fit statistics allow researchers to delve further into the underlying problems experienced by these "atypical" patients treated for Cushing's syndrome. Annotated code is provided to aid other researchers in using this method. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 44% |
| United Kingdom | 2 | 22% |
| Switzerland | 1 | 11% |
| Sweden | 1 | 11% |
| Unknown | 1 | 11% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
| Scientists | 1 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 83 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 19% |
| Researcher | 11 | 13% |
| Student > Master | 11 | 13% |
| Student > Bachelor | 7 | 8% |
| Professor > Associate Professor | 6 | 7% |
| Other | 15 | 18% |
| Unknown | 17 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 20 | 24% |
| Social Sciences | 8 | 10% |
| Medicine and Dentistry | 7 | 8% |
| Business, Management and Accounting | 5 | 6% |
| Engineering | 4 | 5% |
| Other | 16 | 19% |
| Unknown | 23 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 August 2023.
All research outputs
#4,886,638
of 24,208,207 outputs
Outputs from Frontiers in Psychology
#7,901
of 32,536 outputs
Outputs of similar age
#81,173
of 317,142 outputs
Outputs of similar age from Frontiers in Psychology
#215
of 604 outputs
Altmetric has tracked 24,208,207 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 32,536 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,142 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 604 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.