John M Taylor
Biographic Data
| ID | 5770107 |
|---|---|
| NAME | John M Taylor |
| GIVEN NAMES | John M |
| FAMILY NAME | Taylor |
| SIGNATURE | TAYLOR J M |
| AFFILIATIONS | Saint Louis University |
| ORCID | 0000-0002-4275-077X |
| VERIFIED | Yes |
| TOTAL WORKS | 30 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 29 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 1967 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Should We Keep or Remove Outliers
In keeping with this year's focus on outliers, this column entry encourages our community to only consider deleting outliers after a thorough investigation suggests the method is valid. If the preponderance of evidence does not favor removing an outlier, then researchers should retain the observation(s) and turn to alternative outlier management strategies
Check for Outliers
In 2026, the Methodology Corner column will focus on the management of outliers in a valid science of nursing education. Outliers are capable of introducing errors into studies that ignore or mismanage them. This column entry specifically encourages applied researchers to ensure they check each of their studies for outliers and to report their outlier methodology and results well in their research works
Dimensionality and Item-Level Analysis of the Dast-10 in a Sample of HIV Patients with a History of Problematic Substance Use
Questionable Research Practices: P -Hacking
The Methodology Corner has opted to call attention to questionable research practices in 2025. This first column of the year specifically looks at p -hacking. Studies subject to p-hacking may be harmful to the science of nursing education. This article provides recommendations for the nursing education community on how to help prevent p-hacking in the nursing literature. [ J Nurs Educ . 2025;64(3):211–212.]
Questionable Research Practices: Harking
To finish out the Methodology Corner's focus in 2025 on questionable research practices, attention is called to the problem of HARKing. When research works omit that a finding being reported on and explained was discovered post hoc, a number of unwanted problems can ensue. Several strategies are suggested that might help our community manage the problems associated with HARKing
Questionable Research Practices: Cherry Picking
In keeping with the focus on questionable research practices in 2025, this entry of the Methodology Corner calls attention to the practice of cherry picking. Studies subject to cherry picking have the potential to introduce inaccurate information into the nurse education literature. This column highlights a few recommendations our community might utilize to help dissuade the practice of cherry picking. [ J Nurs Educ . 2025;64(7):467–468.]
Adopting Optimal Statistical Practices: Reviewers
In this installment of the Methodology Corner , we briefly discuss how our peer-reviewers might foster optimal statistical practices among our community of researchers. Reviewers are encouraged to seek out training opportunities that enhance their own statistical expertise and to consider tools that might support and enhance the quality of their reviews. We also encourage reviewers with statistical expertise to further lend their time and efforts…
Adopting Optimal Statistical Practices: Applied Researchers
In keeping with this year's focus on how we might foster a culture of research that values and consistently adopts optimal statistical practices, this column entry highlights practices our applied researchers can take up that may help remedy the gap between recommended statistical practices and implementation. This installment specifically encourages increasing the transparency of analyses, teaming up with colleagues with quantitative expertise, …
Adopting Optimal Statistical Practices: Graduate Programs
In 2024, the Methodology Corner will briefly look at how we might foster enduring commitments from nurse education researchers to remain up-to-date on their statistical expertise and to use optimal statistical methods. The first column of the year specifically looks at how graduate programs might enrich their statistics curriculum in a manner that could foster an increasingly valid science of nursing education. [ J Nurs Educ . 2024;63(3):197–198.…
Cohen's and Hedges' g
A cursory review of relevant research works published in the Journal of Nursing Education suggests our community relies heavily on Cohen's d . Although Cohen's d is a valuable effect size, it possesses a number of limitations that warrants our community adopting a wider set of effect size statistics to help promote a valid science of nursing education. We specifically call attention to Hedges' g. [ J Nurs Educ . 2023;62(5):316–317.]
Remember to Leverage Effect Size Estimates
In 2023, the Methodology Corner column has opted to promote the efficacious use of effect sizes among our community of researchers. In this first entry of the year, we call attention to broad improvement in effect size reporting germane to our community, including more consistent reporting of effect sizes and their interpretations. [ J Nurs Educ . 2023;62(2):116.]
Improving Effect Size Interpretations
We encourage our community of nurse education researchers to remember to assign interpretations to their effect size estimates. In general, our community is asked to reduce the use of rules-of-thumb and, instead, are encouraged to use empirical and contextual methods to assign interpretations to effect size estimates. [ J Nurs Educ . 2023;62(11):653–654.]
From η 2 to ω 2: Adopt a Better Measure of Effect
A cursory review of relevant research works published in the Journal of Nursing Education suggests that our community may unnecessarily rely on η 2 when reporting results of their ANOVA models. Although η 2 is convenient, the statistic possesses many limitations that warrant our community adopting a wider set of effect size statistics and practices to promote a valid science of nursing education. We specifically call attention in this article to …
Prevent Problematic Missing Data
Over the course of 2022, we have encouraged our community to adopt increasingly effective methods of mitigating the harm missing data poses to a valid science of nursing education. With our last column entry for the year, we conclude our emphasis by looking at a few approaches to the prevention of problematic missingness that can be implemented prior to collecting data. [ J Nurs Educ . 2022;61(11):657–658.]
Missing Data
If left unattended, missingness can undermine the conclusions nurse researchers draw in their studies. Unfortunately, a cursory review of quantitative and mixed methods works recently published in the Journal of Nursing Education suggests missing data is left relatively unattended within our community. This column has recommended our researcher mitigate the emergence of missing data as much as possible, describe any missingness thoroughly, and ad…
Repair Your Missing Data
This Methodology Corner encourages nurse educators to include reparative techniques in their analyses that better allay threats to validity introduced by missing data. This article specifically highlights the extra dependent variable technique that is accessible to researchers due to the simplicity of the approach and availability of popular software capable of implementing the repair. [ J Nurs Educ . 2022;61(9):549–550.]
Study Your Missing Data
This installment of the Methodology Corner raises the concern that our community may not be adequately attending to the threat missingness poses to valid nursing education research. To encourage the adoption of increasingly sound methodological practices, we highlight for our community that counts and relative frequencies and simple bivariate analyses are easily implemented tools that help formulate valid responses to missing data. [ J Nurs Educ …
Coefficient Omega
This article raises the concern that nursing education research may be unduly subject to several limitations inherited from an overreliance on Cronbach's α. Consequently, researchers are encouraged to make greater use of coefficient omega since it is expected to perform just as well as or better than Cronbach's α, especially when tau-equivalence goes unmet. Several resources are noted that may help researchers estimate omega for composite measure…
More Power Analyses Are Needed
Nurse researchers have long been encouraged to consult a priori power analyses to help design studies that are robust to type II errors. Unfortunately, a cursory look at Journal of Nursing Education articles published in 2020 suggests that a priori power analyses may be used infrequently in our community. Consequently, this column requested that authors conduct power analyses using increasingly rigorous standards (e.g., power levels) and report t…
Reliability
A cursory look at the measurement practices in the Journal of Nursing Education revealed several deficits that our community is encouraged to address. In 2020, a little less than half of our quantitative studies did not provide reliability estimates from their own data, opting instead to provide estimates reported in the literature or none at all. Of the studies that did supply estimates using their data, only Cronbach's alpha was reported. Unfor…
Student perceptions of online and in-person microbiology laboratory experiences in undergraduate medical education
Background : Universities are facing increased budget constraints, often resulting in reduced funds to support microbiology laboratories. Online mock laboratory activities are often instituted as a cost-effective alternative to traditional wet labs for medical students. Objective : The purpose of this study was to examine students' perceptions of online and in-person microbiology lab learning experiences. Design : We investigated undergraduate me…
Psychometric analysis of the Ten-Item Perceived Stress Scale.
Although the 10-item Perceived Stress Scale (PSS-10) is a popular measure, a review of the literature reveals 3 significant gaps: (a) There is some debate as to whether a 1- or a 2-factor model best describes the relationships among the PSS-10 items, (b) little information is available on the performance of the items on the scale, and (c) it is unclear whether PSS-10 scores are subject to gender bias. These gaps were addressed in this study using…
Duty Faithfully Performed: Robert E. Lee and His Critics
Confederate Raider: Raphael Semmes of the Alabama
William Henry Seward: Lincoln's Right Hand
An Approach to the Emergence of Heterodoxy in Mediaeval Islām
Self-righteousness and censoriousness are strong emotions. They exist in the claims of ‘orthodoxy’ as much as in the protests of ‘heterodoxy’. They lie behind claims of tolerance as often as behind displays of intolerance. These emotions should be disentangled in the motives of the men who make history, of those who write history, and of those who read history. The very designation ‘heterodox’ is both etymologically and conceptually structured in…
Garfield of Ohio: The Available Man
Relationship between the Wais-R and the WRAT in a Geriatric Sample with Suspected Dementia
Pearson product-moment correlations between the standard scores of the Wide Range Achievement Test (Spelling, Reading, and Arithmetic) and the WAIS-R Full Scale IQ, Verbal IQ, Performance IQ and the scaled scores of the individual subtests were calculated for a geriatric sample with suspected dementia ( M age = 72.37 yr.). The three areas of achievement, as measured by the Wide-Range Achievement Test, correlated highly with the WAIS-R IQs and sub…
General Maxwell Taylor: The Sword and the Pen
William Henry Seward: Lincoln's Right Hand
Journal Article William Henry Seward: Lincoln's Right Hand. By John M. Taylor. (New York: HarperCollins, 1991. xii + 340 pp. $25.00, ISBN 0-06-016307-0.) Get access Adrian Cook Adrian Cook University of Reading, England Search for other works by this author on: Oxford Academic Google Scholar Journal of American History, Volume 79, Issue 2, September 1992, Page 666, https://doi.org/10.2307/2080105 Published: 01 September 1992
William Henry Seward: Lincoln's Right Hand
Confederate Raider: Raphael Semmes of the Alabama
Duty Faithfully Performed: Robert E. Lee and His Critics
Psychometric analysis of the Ten-Item Perceived Stress Scale.
Although the 10-item Perceived Stress Scale (PSS-10) is a popular measure, a review of the literature reveals 3 significant gaps: (a) There is some debate as to whether a 1- or a 2-factor model best describes the relationships among the PSS-10 items, (b) little information is available on the performance of the items on the scale, and (c) it is unclear whether PSS-10 scores are subject to gender bias. These gaps were addressed in this study using…
Student perceptions of online and in-person microbiology laboratory experiences in undergraduate medical education
Background : Universities are facing increased budget constraints, often resulting in reduced funds to support microbiology laboratories. Online mock laboratory activities are often instituted as a cost-effective alternative to traditional wet labs for medical students. Objective : The purpose of this study was to examine students' perceptions of online and in-person microbiology lab learning experiences. Design : We investigated undergraduate me…
Coefficient Omega
This article raises the concern that nursing education research may be unduly subject to several limitations inherited from an overreliance on Cronbach's α. Consequently, researchers are encouraged to make greater use of coefficient omega since it is expected to perform just as well as or better than Cronbach's α, especially when tau-equivalence goes unmet. Several resources are noted that may help researchers estimate omega for composite measure…
More Power Analyses Are Needed
Nurse researchers have long been encouraged to consult a priori power analyses to help design studies that are robust to type II errors. Unfortunately, a cursory look at Journal of Nursing Education articles published in 2020 suggests that a priori power analyses may be used infrequently in our community. Consequently, this column requested that authors conduct power analyses using increasingly rigorous standards (e.g., power levels) and report t…
Reliability
A cursory look at the measurement practices in the Journal of Nursing Education revealed several deficits that our community is encouraged to address. In 2020, a little less than half of our quantitative studies did not provide reliability estimates from their own data, opting instead to provide estimates reported in the literature or none at all. Of the studies that did supply estimates using their data, only Cronbach's alpha was reported. Unfor…
Prevent Problematic Missing Data
Over the course of 2022, we have encouraged our community to adopt increasingly effective methods of mitigating the harm missing data poses to a valid science of nursing education. With our last column entry for the year, we conclude our emphasis by looking at a few approaches to the prevention of problematic missingness that can be implemented prior to collecting data. [ J Nurs Educ . 2022;61(11):657–658.]
Missing Data
If left unattended, missingness can undermine the conclusions nurse researchers draw in their studies. Unfortunately, a cursory review of quantitative and mixed methods works recently published in the Journal of Nursing Education suggests missing data is left relatively unattended within our community. This column has recommended our researcher mitigate the emergence of missing data as much as possible, describe any missingness thoroughly, and ad…
Repair Your Missing Data
This Methodology Corner encourages nurse educators to include reparative techniques in their analyses that better allay threats to validity introduced by missing data. This article specifically highlights the extra dependent variable technique that is accessible to researchers due to the simplicity of the approach and availability of popular software capable of implementing the repair. [ J Nurs Educ . 2022;61(9):549–550.]
Study Your Missing Data
This installment of the Methodology Corner raises the concern that our community may not be adequately attending to the threat missingness poses to valid nursing education research. To encourage the adoption of increasingly sound methodological practices, we highlight for our community that counts and relative frequencies and simple bivariate analyses are easily implemented tools that help formulate valid responses to missing data. [ J Nurs Educ …
Cohen's and Hedges' g
A cursory review of relevant research works published in the Journal of Nursing Education suggests our community relies heavily on Cohen's d . Although Cohen's d is a valuable effect size, it possesses a number of limitations that warrants our community adopting a wider set of effect size statistics to help promote a valid science of nursing education. We specifically call attention to Hedges' g. [ J Nurs Educ . 2023;62(5):316–317.]
Remember to Leverage Effect Size Estimates
In 2023, the Methodology Corner column has opted to promote the efficacious use of effect sizes among our community of researchers. In this first entry of the year, we call attention to broad improvement in effect size reporting germane to our community, including more consistent reporting of effect sizes and their interpretations. [ J Nurs Educ . 2023;62(2):116.]
Improving Effect Size Interpretations
We encourage our community of nurse education researchers to remember to assign interpretations to their effect size estimates. In general, our community is asked to reduce the use of rules-of-thumb and, instead, are encouraged to use empirical and contextual methods to assign interpretations to effect size estimates. [ J Nurs Educ . 2023;62(11):653–654.]
From η 2 to ω 2: Adopt a Better Measure of Effect
A cursory review of relevant research works published in the Journal of Nursing Education suggests that our community may unnecessarily rely on η 2 when reporting results of their ANOVA models. Although η 2 is convenient, the statistic possesses many limitations that warrant our community adopting a wider set of effect size statistics and practices to promote a valid science of nursing education. We specifically call attention in this article to …
Adopting Optimal Statistical Practices: Reviewers
In this installment of the Methodology Corner , we briefly discuss how our peer-reviewers might foster optimal statistical practices among our community of researchers. Reviewers are encouraged to seek out training opportunities that enhance their own statistical expertise and to consider tools that might support and enhance the quality of their reviews. We also encourage reviewers with statistical expertise to further lend their time and efforts…
Adopting Optimal Statistical Practices: Applied Researchers
In keeping with this year's focus on how we might foster a culture of research that values and consistently adopts optimal statistical practices, this column entry highlights practices our applied researchers can take up that may help remedy the gap between recommended statistical practices and implementation. This installment specifically encourages increasing the transparency of analyses, teaming up with colleagues with quantitative expertise, …
Adopting Optimal Statistical Practices: Graduate Programs
In 2024, the Methodology Corner will briefly look at how we might foster enduring commitments from nurse education researchers to remain up-to-date on their statistical expertise and to use optimal statistical methods. The first column of the year specifically looks at how graduate programs might enrich their statistics curriculum in a manner that could foster an increasingly valid science of nursing education. [ J Nurs Educ . 2024;63(3):197–198.…
Questionable Research Practices: P -Hacking
The Methodology Corner has opted to call attention to questionable research practices in 2025. This first column of the year specifically looks at p -hacking. Studies subject to p-hacking may be harmful to the science of nursing education. This article provides recommendations for the nursing education community on how to help prevent p-hacking in the nursing literature. [ J Nurs Educ . 2025;64(3):211–212.]
Psychology (19 works) · Computer Science (16 works) · Mathematics (9 works) · Column (typography) (8 works) · Meta-analysis and systematic reviews (7 works) · Political science (7 works) · Statistics (7 works) · Data science (5 works) · History (5 works) · History (5 works)