Survey data was used to develop univariate and multivariate logistic regression models for six outcome variables originating from the items assessing the acceptance of specific types of eHealth applications. (springer.com)
Univariate logistic regression models developed for six types of eHealth solutions demonstrated their higher acceptance among younger respondents, living in urban areas, who have attained a higher level of education, used the Internet on their own, and were more confident about its usefulness in making health-related decisions. (springer.com)
The univariate analysis and multivariate logistic regression were used to analyze the cross-sectional data. (plos.org)
We begin our discussion with a familiar framework, a univariate logistic regression model for dichotomous outcomes. (routledgehandbooks.com)
Univariate, multivariate, receiver operator characteristic and correlation analyses were performed to select final predictors. (bmj.com)
Analyses6
A multivariate logistic regression model was used for data analyses. (nih.gov)
Kaplan-Meier and Cox regression analyses were used to compare progression free survival (PFS) and overall survival (OS) between the groups. (springer.com)
Logistic regression and multiple correspondence analyses were used to explore the relationships among multidomain lifestyles, chronic diseases, and dementia. (frontiersin.org)
Descriptive statistics and Cox proportional hazards model were used in the analyses. (jcancer.org)
Because stratified analyses suggested that the effect of BMI on arthritis differed by sex, the model was applied separately to men and women. (cdc.gov)
Descriptive statistical analyses and multivariate logistic regression modeling were conducted. (cdc.gov)
Analysis12
Regression analysis often treats category membership with one or more quantitative dummy variables. (wikipedia.org)
In the second instance all the analyzed values were included in logistic regression model for multivariate analysis. (sages.org)
We do not discuss limited-information estimation methods derived from categorical factor analysis or structural equation modeling (see, e.g. (routledgehandbooks.com)
Next, we conducted a sex-specific analysis for obesity and its associated factors using backward elimination multivariate logistic regression models. (cdc.gov)
Multivariate analysis was used to assess whether the project was associated with changes in young people's sexual initiation, safer-sex behavior and discussion of reproductive health issues with adults. (guttmacher.org)
Logistic regression analysis showed that compared with sedentary behavior, all levels of leisure-time physical activities lowered the likelihood of filling an antibiotic prescription. (lww.com)
In logistic regression analysis older age, living away from home, smoking by family and close friends and exposure to tobacco promotion were predictors of current smoking status. (who.int)
Statistical5
The identity of a particular word (e.g., in a language model): One of V possible choices, for a vocabulary of size V. For ease in statistical processing, categorical variables may be assigned numeric indices, e.g. 1 through K for a K-way categorical variable (i.e. a variable that can express exactly K possible values). (wikipedia.org)
Baker & Kim, 2004) have been dedicated to the discussion of statistical parameter estimation techniques for item response theory (IRT) models. (routledgehandbooks.com)
We assume that the reader is familiar with elementary probability concepts such as prior, posterior, and likelihood, as well as the equations for describing statistical models for categorical observed data, for example, logistic regression. (routledgehandbooks.com)
For the sake of simplicity, we contextualize our discussion with unidimensional logistic IRT models for dichotomously scored outcomes, but the missing data formulation applies generally across a far wider range of statistical modeling frameworks, IRT modeling included. (routledgehandbooks.com)
A data of 2030 patients with diagnosis of ACS hospitalized from December 2008 to December 2011 was used to develop a risk model based on echocardiographic parameters using the binary logistic regression. (hindawi.com)
Association between independent and dependent variables was analyzed using binary logistic regression model. (who.int)
Variance1
Its association with non-HIV-specific (demographic, socio-economic, behavioral, health status), HIV-specific factors (immuno-viral markers, antiretrovirals, level of perceived HIV-stigma), and HIV-status was assessed using Poisson regression models with robust variance in women and men separately. (nature.com)
Progression2
Objectives To identify the predictive clinical characteristics and establish a prediction model for the progression of mild interstitial lung disease (ILD) in patients with systemic sclerosis (SSc). (bmj.com)
A prediction model for ILD progression was established in the derivation cohort and validated in the multinational validation cohort. (bmj.com)
Estimation1
That is, the latent variables in IRT models are missing data, and had the latent variable scores been available, estimation for IRT models would have been a rather straightforward task. (routledgehandbooks.com)
Variables4
However, when combined in multivariate models, only the belief in the usefulness of the Internet (five of six models), level of education (four of six models), and previous hospitalization due to chronic disease (three of six models) maintained the effect on the independent variables. (springer.com)
Significant variables from the baseline sample were used to build multivariate logistic regression models. (cdc.gov)
We modeled the association between maternal employment and depressive symptoms using multivariate logistic regression, including social support and other control variables. (jabfm.org)
We constructed logistic regression models for current among other racial/ethnic groups (2), and people with low incomesmoking with 6 indicators of food distress as exposure variables or low educational attainment are more likely to smoke than and sociodemographic characteristics, depression, anxiety, per- people with higher socioeconomic status (2,3). (cdc.gov)
Outcomes4
Although number of risk scores have been developed to predict short and long term outcomes in patients with ACS [ 1 - 10 ], GRACE and TIMI risk scores are the most popular and validated ACS prediction models, recommended by contemporary guidelines [ 11 , 12 ]. (hindawi.com)
Chae YK, Brown EN, Lei X, Melhem-Bertrandt A, Giordano SH, Litton JK, Hortobagyi GN, Gonzalez-Angulo AM, Chavez-MacGregor M. Use of ACE Inhibitors and Angiotensin Receptor Blockers and Primary Breast Cancer Outcomes. (jcancer.org)
Objectives To create a model that provides a potential basis for candidate selection for anti-tumour necrosis factor (TNF) treatment by predicting future outcomes relative to the current disease profile of individual patients with ankylosing spondylitis (AS). (bmj.com)
The matrix model predicted outcomes as well as algorithm-based models and enabled direct comparison of the effect size of anti-TNF treatment outcome in various subpopulations. (bmj.com)
Methods1
There has also been much recent development in the technical literature on improved methods for estimating complex IRT models (e.g. (routledgehandbooks.com)
Parameters1
Combining demographic, immune and viral parameters, the best predictive models for mortality comprised IFNB1 or age, viral ORF7a and ACE2 receptor transcripts. (nature.com)
Analyze1
Based on market basket data, multicategory purchase incidence models analyze demand interdependencies between product categories. (repec.org)
Evaluate3
To explore the establishment of nomogram prediction model for the risk of no-reflow after percutaneous coronary intervention in patients with acute myocardial infarction and to evaluate the discrimination and accuracy of the model. (ijpsonline.com)
Multivariate logistic regression was used to evaluate a multiplicative model of interaction. (uni-muenchen.de)
however, models to date have not incorporated the ability to evaluate co-exposures with carbon monoxide. (cdc.gov)
Candidate1
Candidate predictors for multivariate logistic regression were selected by expert opinion based on clinical significance. (bmj.com)
Assess1
Multivariate logistic regression was used to assess the relation between self-reported arthritis and age, race, ethnicity, education, and BMI. (cdc.gov)
Odds2
In the multivariate model, the odds of having a topical fluoride application was higher in children who reported brushing teeth more often (OR = 1.62, 95% CI = 1.22, 2.15) and in children from families with better socio-economic position (OR = 1.26, 95% CI = 1.06, 1.50). (uwi.edu)
Multivariate logistic regression was performed to predict the odds of developing hypothyroidism. (medscape.com)
Prediction9
The derived SPAR model combining both predictors (SPO 2 and ARthritis) increased the prediction rate from 25.5% to 91.7% with an area under the curve (95% CI) of 0.83 (0.73 to 0.93). (bmj.com)
Conclusions The evidence-based SPAR prediction model developed in our study might be helpful for the risk stratification of patients with mild SSc-ILD in clinical practice and cohort enrichment for future clinical trial design. (bmj.com)
The risk factors of no-reflow were screened by single factor and multi factor logistic regression model and the nomogram prediction model of no-reflow risk was established based on the risk factors. (ijpsonline.com)
The area under receiver operating characteristic curve was used to test the prediction effect of the model. (ijpsonline.com)
The area under receiver operating characteristic curve was 0.860 with the maximum of Youden index as the best critical value of the prediction model. (ijpsonline.com)
Based on the risk factors affecting no-reflow after percutaneous coronary intervention in patients with acute myocardial infarction, including the number of coronary artery lesions, ischemic time, neutrophil percentage, white blood cell count, thrombus grade and vasospasm grade, this study established a nomogram prediction model. (ijpsonline.com)
The model has good discrimination and consistency and can provide certain guidance for the prediction and preventive intervention of the risk of no-reflow after percutaneous coronary intervention. (ijpsonline.com)
Matrix and algorithm-based prediction models were created using logistic and linear regression, and their accuracies were compared. (bmj.com)
Data from registry populations were applied to study how a daily practice AS population is distributed over the prediction model. (bmj.com)
Mixture2
We propose a finite mixture multivariate logit model to derive segment-specific intercategory effects of market basket purchase. (repec.org)
Toxicological data or PBPK models were not available for the complete mixture of concern. (cdc.gov)
Factors6
Risk factors were examined via multivariate logistic regression techniques. (cdc.gov)
According to the risk factors affecting no-reflow screened by multivariate logistic regression, a nomographic model for predicting the risk of no-reflow was established by using R software (R 3.6.3) regression modeling strategies package. (ijpsonline.com)
Related factors were selected and analysed based on the Andersen Health Seeking Behaviour model. (omicsonline.org)
Multivariate logistic regression was used to identify independent factors associated with late ANC. (omicsonline.org)
To examine the relative importance of these factors, CDC used data from the 1989-1991 National Health Interview Survey (NHIS) and a multivariate model to estimate the independent effect of each factor on self-reported arthritis. (cdc.gov)
Further outcome studies will soon be underway and may in future contribute to adequately integrate all potential factors in more reliable predictive models. (bmj.com)
Independently2
Multivariable logistic regression indicated that wearing long pants or skirts was independently protective against leptospirosis infection (OR adjusted = 0.217), while the presence of more than two wounds on the body was independently associated with infection (OR adjusted = 3.97). (cdc.gov)
This model was independently evaluated in validation cohort prospectively (954 patients admitted during 2012). (hindawi.com)
Linear2
Associations were tested using multivariate linear and logistic regression models. (lu.se)
regression models: simple linear regression, multivariate linear regression and logistic regression. (lu.se)
Data4
We analyzed the data using various discrete choice models, the best-fitting of which was the random parameter (or mixed) logit model with interactions, which enabled us to capture both unobserved and observed heterogeneity in farm households' preferences for the compensation plan attributes. (repec.org)
We developed a flexible model and interactive dashboard of capacity planning for whole-population RPM-based care for T1D.Data were gathered from a weekly RPM program for 277 paediatric patients with T1D at a paediatric academic medical centre. (stanford.edu)
Based on these metrics, an interactive model was designed to facilitate capacity planning and deployed as a dashboard.The primary population-level drivers of demand are the number of patients in the program, the rate at which patients enrol and graduate from the program, and the average frequency at which patients require a review of their data. (stanford.edu)
Toxicological data or PBPK models were not available for any of the three- or four-component submixtures. (cdc.gov)
Clinical1
Incorporation of such developed model should facilitate research, clinical decisions, and optimizing treatment strategy in selected high risk ACS patients. (hindawi.com)
Chronic1
All these circumstances trigger intensive searches for new models of care which would enable an adequate and cost-effective support offered to patients with chronic diseases. (springer.com)
Study1
We deployed this model as an interactive dashboard and used it to facilitate expansion of a novel care program (4 T Study) for newly diagnosed patients with T1D. (stanford.edu)
Interaction1
We find that a homogeneous model would overestimate the intensity of interaction between product categories. (repec.org)
Facilitate1
This model may facilitate the systematic design of RPM-based care programs. (stanford.edu)
Final model1
an aggregate value for job strain was entered into the final model. (cdc.gov)
Approaches1
At the institution studied, the model identified a variety of practical operational approaches to better match the demand for patient care.We designed a generalizable, systematic model for capacity planning for a paediatric endocrinology clinic providing RPM for T1D. (stanford.edu)
Good1
This result is applied to a maximization problem with indivisible durable goods as well as to a Ramsey model with an indivisible consumption good. (repec.org)
Care1
A quantitative model to ensure capacity sufficient for timely access to care in a remote patient monitoring program. (stanford.edu)
Categories1
Models using different BMI categories and models run without proxy-reported observations yielded similar findings. (cdc.gov)
Generally1
PBPK models for methylene chloride generally contain components describing the metabolism of methylene chloride to formaldehyde and carbon monoxide, but to date have not included estimations of co-exposure to either of these compounds. (cdc.gov)