Evaluation of potential predictor variables for PCR assay diagnosis ofAnaplasma phagocytophiluminfection in equids in Northern California

Tests for comparing the strength of association between a variable, X1, and each of two potential predictor variables, X2 and X3, are proposed and examined in a simulation study. The variances of X2 and X3 and the correlation between X2 and X3 are nuisance parameters. A simple modification of a test proposed by Williams (1959) is found to have reasonable properties for a wide range of parameter values and both normal and nonnormal distributions.

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DEVELOPMENT AND VALIDATION OF A FECAL PCR ASSAY FOR NOTOEDRES CATI AND APPLICATION TO NOTOEDRIC MANGE CASES IN BOBCATS (LYNX RUFUS) IN NORTHERN CALIFORNIA, USA

Journal of Wildlife Diseases ◽

10.7589/2012-05-136 ◽

2013 ◽

Vol 49 (2) ◽

pp. 303-311 ◽

Cited By ~ 11

Author(s):

Nicole Stephenson ◽

Deana Clifford ◽

S. Joy Worth ◽

Laurel E. K. Serieys ◽

Janet Foley

Keyword(s):

Lynx Rufus ◽

Northern California ◽

Pcr Assay ◽

Notoedres Cati ◽

Development And Validation ◽

Notoedric Mange

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Prediction of COVID 19 and Its Economic Impact in Africa

10.20944/preprints202104.0767.v1 ◽

2021 ◽

Author(s):

Habte Tadesse Likassa

Keyword(s):

Population Density ◽

Predictor Variables ◽

Spatial And Temporal Variation ◽

Spatial Effects ◽

African Countries ◽

Potential Predictor ◽

Significant Difference ◽

Factor Design ◽

The One ◽

The Impact

This paper presents a two-way factor design incorporating both spatial and temporal variation in the prediction of COVID 19 in Africa. In line with this, the impact of COVID-19on the GDP in Africa is well scrutinized. In contrast to the existing works [1–3], this work also extends the two-factor design into the one-way factor design through incorporating covariates into spatial effects. The data rely on the spatial and temporal obtained from WHO datasets [4, 5]. The one-factor design with more covariates is taken into consideration to identify the major potential predictor variables responsible for the deaths and confirmed cases due to COVID 19 in Africa. The MANCOVA considered population density, temperature, humidity; perception, and wind are all considered as co-variates. Simulations show that the two-way analysis of variance has shown that there is a statistically significant difference between the spatial (Fcal= 8.2704, Pvalue= 3.099&lowast;10−6)and temporal (Fcal= 48.7964, Pvalue= 9.147&lowast;10−16) effects. South Africa and Nigeria are highly influencing due to the pandemic where their GDP also relatively mostly declined. A significant economic change is observed before the pandemic and after the outbreak of the pandemic(tcal= 2.9548, Pvalue= 0.01805). COVID 19 negatively influenced the economy of1 most of the African countries. The population density, temperature, and wind are found to be statistically significantly associated with COVID 19 cases and deaths.

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Predict the Medicare Functional Classification Level (K-level) using the Amputee Mobility Predictor in people with unilateral transfemoral and transtibial amputation: A pilot study

Prosthetics and Orthotics International ◽

10.1177/0309364617706748 ◽

2017 ◽

Vol 42 (2) ◽

pp. 191-197 ◽

Cited By ~ 9

Author(s):

Michael P Dillon ◽

Matthew J Major ◽

Brian Kaluf ◽

Yuri Balasanov ◽

Stefania Fatone

Keyword(s):

Logistic Regression ◽

Pilot Study ◽

Patient Characteristics ◽

Ordinal Logistic Regression ◽

Predictor Variables ◽

Functional Classification ◽

Transfemoral Amputation ◽

Potential Predictor ◽

Younger Age ◽

Representative Samples

Background: While Amputee Mobility Predictor scores differ between Medicare Functional Classification Levels (K-level), this does not demonstrate that the Amputee Mobility Predictor can accurately predict K-level. Objectives: To determine how accurately K-level could be predicted using the Amputee Mobility Predictor in combination with patient characteristics for persons with transtibial and transfemoral amputation. Study design: Prediction. Method: A cumulative odds ordinal logistic regression was built to determine the effect that the Amputee Mobility Predictor, in combination with patient characteristics, had on the odds of being assigned to a particular K-level in 198 people with transtibial or transfemoral amputation. Results: For people assigned to the K2 or K3 level by their clinician, the Amputee Mobility Predictor predicted the clinician-assigned K-level more than 80% of the time. For people assigned to the K1 or K4 level by their clinician, the prediction of clinician-assigned K-level was less accurate. The odds of being in a higher K-level improved with younger age and transfemoral amputation. Conclusion: Ordinal logistic regression can be used to predict the odds of being assigned to a particular K-level using the Amputee Mobility Predictor and patient characteristics. This pilot study highlighted critical method design issues, such as potential predictor variables and sample size requirements for future prospective research. Clinical relevance This pilot study demonstrated that the odds of being assigned a particular K-level could be predicted using the Amputee Mobility Predictor score and patient characteristics. While the model seemed sufficiently accurate to predict clinician assignment to the K2 or K3 level, further work is needed in larger and more representative samples, particularly for people with low (K1) and high (K4) levels of mobility, to be confident in the model’s predictive value prior to use in clinical practice.

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In vivo detection of vertical root fractures in endodontically treated teeth: Accuracy of cone-beam computed tomography and assessment of potential predictor variables

Journal of Clinical and Experimental Dentistry ◽

10.4317/jced.57471 ◽

2021 ◽

pp. 0-0

Author(s):

M. Quintero-Álvarez ◽

L. Bolaños-Alzate ◽

P. Villa-Machado ◽

F. Restrepo-Restrepo ◽

S. Tobón-Arroyave

Keyword(s):

Computed Tomography ◽

Cone Beam Computed Tomography ◽

Predictor Variables ◽

Cone Beam ◽

Endodontically Treated Teeth ◽

Potential Predictor ◽

In Vivo Detection ◽

Root Fractures

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Psychological Adjustment in Spain during the COVID-19 Pandemic: Positive and Negative Mental Health Outcomes in the General Population

The Spanish Journal of Psychology ◽

10.1017/sjp.2021.7 ◽

2021 ◽

Vol 24 ◽

Cited By ~ 2

Author(s):

Carmen Valiente ◽

Alba Contreras ◽

Vanesa Peinado ◽

Almudena Trucharte ◽

Antón P. Martínez ◽

...

Keyword(s):

Mental Health ◽

Substance Use ◽

Logistic Regression ◽

Mortality Rate ◽

General Population ◽

Psychological Adjustment ◽

Well Being ◽

Predictor Variables ◽

Potential Predictor ◽

Anxiety Depression

Abstract In the midst of the COVID–19 epidemic, Spain was one of the countries with the highest number of infections and a high mortality rate. The threat of the virus and consequences of the pandemic have a discernible impact on the mental health of citizens. This study aims to (a) evaluate the levels of anxiety, depression and well-being in a large Spanish sample during the confinement, (b) identify potential predictor variables associated to experiencing both clinical levels of distress and well-being in a sample of 2,122 Spanish people. By using descriptive analyses and logistic regression results revealed high rates of depression, anxiety and well-being. Specifically, our findings revealed that high levels of anxiety about COVID–19, increased substance use and loneliness as the strongest predictors of distress, while gross annual incomes and loneliness were strongest predictors of well-being. Finding of the present study provide a better insight about psychological adjustment to a pandemic and allows us to identify which population groups are at risk of experiencing higher levels of distress and which factors contribute to greater well-being, which could help in the treatments and prevention in similar stressful and traumatic situations.

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Prediction of Outstanding Achievement in the Natural Sciences

Gifted Education International ◽

10.1177/026142949801300203 ◽

1998 ◽

Vol 13 (2) ◽

pp. 106-112 ◽

Cited By ~ 1

Author(s):

Joachim Sieglen ◽

Günter Trost

Keyword(s):

Career Decisions ◽

Natural Sciences ◽

Predictor Variables ◽

Outstanding Achievement ◽

Distinctive Features ◽

Potential Predictor ◽

Upper Secondary ◽

Scholarship Program ◽

Nationally Representative ◽

And Mathematics

The Institute for Test Development and Talent Research is conducting a longitudinal study which started in 1973 on a nationally representative sample of 9,000 persons who then graduated from upper secondary sehool and were followed up ever since at five-to-six-year intervals. Out of this sample and, in addition, out of the former scholars of the most selective German national scholarship program, 40 persons were identified who had, by their mid-thirties and later on, achieved outstanding and influential research results in the natural scienees. This group was compared with the total representative group in terms of a number of potential predictor variables. The most distinctive features were: The outstanding scientists had achieved much higher performance both in sehool and in university. They pursued to a higher extent curricular and extracurricular interests in the areas of natural sciences and mathematics during adolescence. They were much more inclined to tackle intellectual problems (and did so more sucessfully), and they participated more frequently in academic competitions. They had and have a much higher professional motivation: their career decisions were more heavily based on intrinsic and achievement-oriented motives, and the average time per week they devote to their work is considerably higher.

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