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Mendeley readers
Attention Score in Context
| Title |
Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
|
|---|---|
| Published in |
Frontiers in Psychology, January 2012
|
| DOI | 10.3389/fpsyg.2012.00322 |
| Pubmed ID | |
| Authors |
Kim F. Nimon |
| Abstract |
The validity of inferences drawn from statistical test results depends on how well data meet associated assumptions. Yet, research (e.g., Hoekstra et al., 2012) indicates that such assumptions are rarely reported in literature and that some researchers might be unfamiliar with the techniques and remedies that are pertinent to the statistical tests they conduct. This article seeks to support researchers by concisely reviewing key statistical assumptions associated with substantive statistical tests across the general linear model. Additionally, the article reviews techniques to check for statistical assumptions and identifies remedies and problems if data do not meet the necessary assumptions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 341 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hungary | 2 | <1% |
| Portugal | 1 | <1% |
| Colombia | 1 | <1% |
| Netherlands | 1 | <1% |
| Finland | 1 | <1% |
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 333 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 67 | 20% |
| Student > Master | 57 | 17% |
| Student > Bachelor | 41 | 12% |
| Student > Doctoral Student | 34 | 10% |
| Researcher | 26 | 8% |
| Other | 51 | 15% |
| Unknown | 65 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 80 | 23% |
| Social Sciences | 30 | 9% |
| Business, Management and Accounting | 29 | 9% |
| Agricultural and Biological Sciences | 29 | 9% |
| Medicine and Dentistry | 13 | 4% |
| Other | 88 | 26% |
| Unknown | 72 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 28 August 2012.
All research outputs
#23,381,499
of 25,998,826 outputs
Outputs from Frontiers in Psychology
#27,800
of 34,802 outputs
Outputs of similar age
#235,032
of 256,169 outputs
Outputs of similar age from Frontiers in Psychology
#408
of 485 outputs
Altmetric has tracked 25,998,826 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 34,802 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 256,169 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 485 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.