BivariateMultivariable logistic regressionMultivariate logistic regressionLogistic regressionsStepwiseVariablesCorrelationMethodsOrdinary Least SUnivariateCoefficientResultsMultipleModelsPredictDataVariationSquaresModelDeterminantsAppendixLinearConsumptionVariableAssociationsFactorsQualitativeFindingsAssessExhibitDatasetSimplePowerEnablesFoundIdentificationCharacteristicsRelationshipTheoryExposureOutcomes
Bivariate6
- Bivariate and multiple logistic regression analyses examined the associations at a 5% level of statistical significance. (springer.com)
- Simple logistic regressions established bivariate associations between explanatory and outcome variables. (cdc.gov)
- Explanatory variables significantly associated with the outcome in the bivariate analyses were used to fit a multivariable logistic regression model. (cdc.gov)
- Bivariate and multivariable logistic regression analyses using generalized estimating equations were employed to examine associations between various intersecting socio-structural factors and suicidality. (ubc.ca)
- Variables with - value less than 0.25 in bivariate regression were the candidate for the final multivariate logistic regression. (hindawi.com)
- We assess bivariate inequities using a regression-based decomposition method. (bvsalud.org)
Multivariable logistic regression1
- Multivariable logistic regression analysis was conducted to investigate risk factors statistically associated with the infection status (AIV and H5). (cdc.gov)
Multivariate logistic regression2
- Multivariate logistic regression analysis to predict the presence of halitosis, found periodontal disease was a significant predictor of halitosis (OR = 3.607, 95% CI 1.023-12.718, p = 0.046). (nature.com)
- This was verified by the multivariate logistic regression analysis where "taking part in other sports than ice hockey" was the explanatory variable that showed the strongest association with the dependent variable. (nih.gov)
Logistic regressions1
- Explanatory variables with a p-value below 0.2 were selected to be included in multivariable logistic regressions. (cdc.gov)
Stepwise2
- Data were analyzed using frequency distribution and stepwise multiple regression analysis. (ed.gov)
- Two stepwise multiple linear regression analyses were conducted. (bvsalud.org)
Variables24
- An example of a spurious relationship can be found in the time-series literature, where a spurious regression is one that provides misleading statistical evidence of a linear relationship between independent non-stationary variables. (wikipedia.org)
- There are potentially some data quality issues around the variables used in the analysis, which may influence the conclusions. (bmj.com)
- Pairwise collinearity was tested between all selected explanatory variables by computing Cohen's kappa coefficient and considered significant if the absolute value of the coefficient exceeded 0.7. (cdc.gov)
- The association between the probability of presence of FoG and possible explanatory variables was assessed by logistic regression analysis. (frontiersin.org)
- The main explanatory variables of FoG occurrence are levodopa equivalent dose, age, age at disease onset, and WCST. (frontiersin.org)
- Regressions explain the variation in logarithm of total consumption (or expenditure) per capita by selected explanatory variables. (worldbank.org)
- In a nutshell: the applicant must fill a concept sheet detailing the team in charge of the analysis, the analysis plan, and the variables needed for the analysis. (unige.ch)
- To explain these distribution patterns of median seed mass, we applied multiple regression analyses on twelve selected environmental variables, accounting for spatial autocorrelation. (ufz.de)
- To deal with collinearities of the predictors, we used hierarchical partitioning to analyze the independent and joint explanatory power of the environmental variables. (ufz.de)
- On the existence of time lags between changes in real estate prices and explanatory macroeconomic variables. (upm.es)
- Based on previous studies conducted in Colorado and neighboring States and on the availability of data, 72 characteristics (57 basin and 15 climatic characteristics) were evaluated as candidate explanatory variables in the regression analysis. (usgs.gov)
- Several studies attempted to explore different variables to determine the explanatory power of proxies in predicting stock return. (ccsenet.org)
- This study aims at examining the predicting power in the U.K. equity market by plugging into the regression model some of the variables conventionally measured in the Structural Equation Modeling. (ccsenet.org)
- The emphasis is placed in linear models with one or more explanatory variables, but the module also includes a number of non-linear models. (kau.se)
- The PLS discriminant analysis uses the PLS algorithm to explain and predict the membership of observations to several classes using quantitative or qualitative explanatory variables. (xlstat.com)
- For example, when the number of observations is low and when the number of explanatory variables is high. (xlstat.com)
- Finally, as PLS regression, it is adapted when multicollinearity between explanatory variables is high. (xlstat.com)
- The second analysis took the type of orientation as explanatory variables. (bvsalud.org)
- relate questions regarding random variation and observed data, as they appear in applications, to the concepts of random variables, distributions, and relationships between variables, · examine a statistical model and its ability to describe reality, · examine a simple measurement situation and judge whether data is collected in a way that allows further analysis. (lu.se)
- Correlation between two explanatory variables. (lu.se)
- Most physicians are familiar with the simplest form of regression analysis, simple linear regression, which describes the linear relationship between 2 variables. (medscape.com)
- It is assumed that on each individual are available values of one or more explanatory variables. (who.int)
- The hazard function (age-specific failure rate) is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time. (who.int)
- Logistic regression analysis and hierarchical selection of variables were used to verify the associated factors. (bvsalud.org)
Correlation4
- More complex analyses, however, may require multiple data sets and the search for a correlation using regression analysis. (econsultancy.com)
- Spearman's correlation coefficient and linear regression analysis were conducted. (medicaljournals.se)
- Associations among factors were assessed through correlation analysis, and binary logistic regression was done to predict childhood acute respiratory infections. (hindawi.com)
- Correlation analysis found the strongest relationships between the UHI and population (log P). Regression models using log P alone could explain 65-67% of the variability of UHIs in the region. (nersc.no)
Methods6
- Methods Univariate and multivariate linear regression models were used to show relationships between the outcome measures and various measures of trust activity including empty day beds, empty night beds, day bed to night bed ratio, ED conversion ratio and delayed transfers of care. (bmj.com)
- They have proven that remote sensing data using statistical methods, such as principal component analysis (PCA) and cluster analysis (CA), is a useful and promising method to monitor and predict salt-affected soils, especially those with high salinity. (scirp.org)
- Traditional methods of direct tissue analysis or the use of handheld meters, are not able to capture chlorophyll variability at anything beyond point scales, so are not particularly useful for informing decisions on plant health and status at the field scale. (mdpi.com)
- The mixed methods sequential explanatory design was used in this study. (ed.gov)
- Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. (karger.com)
- A review of surveys conducted to date reveals considerable variation in both the choice and use of survey methods and in the assumptions made in the analysis and interpretation of findings. (who.int)
Ordinary Least S1
- We apply probit, ordinary least squares, and tobit multivariate regression analyses to the three waves in which NCMS was active (2006, 2009 and 2011). (biomedcentral.com)
Univariate2
- Results Univariate regression results using the outcome of 4-hour breaches showed clear relationships with empty night beds and ED conversion ratio between 2012 and 2016. (bmj.com)
- Our analysis reveals that, empirically, different definitions of health inequity do not yield statistically significant differences in the estimated amount of univariate inequity. (bvsalud.org)
Coefficient1
- Based on these results and combining the spectral indices (PC2 and abs B4) into a regression analysis , model yielded a relatively high coefficient of determination R 2 = 0.62 and a low RMSE = 1.86 dS/m. (scirp.org)
Results5
- Logistic regression results indicate that controlling for current age, year of birth, education, marital status in 1973, and race, men who retire early die sooner than men who retire at age 65 or older. (ssa.gov)
- Regression results also indicate that the composition of the early retirement variable matters. (ssa.gov)
- Regression results suggest this is partly explained by reimbursement for chronic diseases. (biomedcentral.com)
- The fundamental knowledge is essential for those who, in their professional lives, will not necessarily be involved in statistical analyses on a daily basis, but who, on occasion, will be expected to perform basic statistical tests and present the results to their colleagues. (lu.se)
- In the sensitivity analysis of those with BMI data, adjustment for BMI somewhat attenuated the results, but the findings were not meaningfully changed. (medscape.com)
Multiple4
- And spreadsheets don't incorporate advanced technologies that can leverage multiple data sources and predictive capabilities, such as detailed, what-if analysis. (oracle.com)
- The adaptation of correspondence analysis for to the integration of multiple tables is similar to the method for single tables with additional matrix concatenation operations. (ne.jp)
- The data is taken from the Guotaian database, some of which is obtained by manually reading the company's annual report, and a multiple regression analysis model is established and tested. (hindawi.com)
- Multiple regression is an extension of this technique, in which more than one independent variable is used to describe a single, continuous dependent variable. (medscape.com)
Models5
- The first hitting time of a boundary or threshold by the sample path of a stochastic process is the central concept of threshold regression models for survival data analysis. (umd.edu)
- Regression functions for the process and threshold parameters in these models are multivariate combinations of explanatory variates. (umd.edu)
- The identifiability issue is confronted directly in threshold regression but is also present when applying other kinds of models commonly used for survival data analysis. (umd.edu)
- construct a simple statistical model describing a problem based on a real life situation or on a collected data material, · use a computational program for simulation and interpretation of statistical models, as well as for data analysis, · choose, modify, perform, and interpret a statistical procedure that answers a given statistical problem, · use statistical terms within the field in writing. (lu.se)
- This derives from the relatively small explanatory power common in regression models describing variations in health. (bvsalud.org)
Predict1
- This study will explore the potential multivariate statistical analysis , such as principal component analysis (PCA) and cluster analysis to identify the most correlated spectral indices and rapidly predict salt affected soils. (scirp.org)
Data15
- Design Linear regression analysis of routinely reported trust activity and performance data using a series of cross-sectional studies. (bmj.com)
- We analyse the change in the importance of common explanatory theories of hospital flow bottlenecks across 5 years using recent openly published data. (bmj.com)
- The principal components analysis is conducted by incorporating the reflectance bands and spectral salinity indices from the remote sensing data. (scirp.org)
- The analyst also needs to make it clear what data is relevant to the analysis so that the relationship between the two data sets is clear. (econsultancy.com)
- And, when comparing data sets looking for a relationship, statistical analysis may be required for a diagnoses, specifically regression analysis (see point 2 below). (econsultancy.com)
- More advanced techniques in this area include data mining and principal component analysis, but straightforward regression analysis is a great place to get started. (econsultancy.com)
- Finally, Quantile Regression is presented, along with an example utilizing the Boston Housing data set. (wikibooks.org)
- In addition, we use the web analysis tool Matomo, which tracks data anonymously. (ufz.de)
- We show, using both theoretical analysis and case demonstrations, that model estimates derived from typical survival data may not be able to distinguish between individuals in the cure rate fraction who are not susceptible to failure and those who may be susceptible to failure but escape the fate by chance. (umd.edu)
- To make further reductions in the uncertainties of the peak-streamflow regional-regression equations in the Foothills and Plains hydrologic regions, additional streamgages or crest-stage gages are needed to collect peak-streamflow data on natural streams in eastern Colorado. (usgs.gov)
- second, the estimated m is used for log- F -penalized logistic regression analyses of all variants using data augmentation with standard software. (karger.com)
- When there are missing values, PLS discriminant analysis can be applied on the data that is available. (xlstat.com)
- Data analysis included use of logistic regression stratified by sex and prediabetes/diabetes status to model odds of behavior by physician advice. (cdc.gov)
- One sensitivity analysis examined the association across strata of glycated hemoglobin (A1c), and another also adjusted for BMI in the subpopulation that had BMI data available. (medscape.com)
- Paper III was a Grounded Theory study that used data from 7 focus group discussions conducted among 28 students at Lund University to explore conceptualisations and organisational structures as explanatory mechanisms for sexual harassment. (lu.se)
Variation3
- The performed regression analysis thus confirms the important role of the surrounding temperature in explaining spatial-temporal variation of UHI intensity. (nersc.no)
- The explanatory power of dividends in the regression analysis showed a significant variation when the analysis follows time-series methodology. (ccsenet.org)
- The course is intended to give the student the basics in mathematical modelling of random variation and an understanding of the principles behind statistical analysis. (lu.se)
Squares1
- Generalized-Least Squares regression was used to compute the final peak-streamflow regional-regression equations for peak-streamflow. (usgs.gov)
Model3
- The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis. (emerald.com)
- Using the multivariate regression model, we identified the association of SME and the government policy factors on the creation of employment. (mdpi.com)
- Slightly incorrect specifications for regression functions or for the stochastic process can lead to problems with model identification and estimation. (umd.edu)
Determinants2
- Separate analysis of determinants of pulmonary function within these subgroups resulted in distinctly different patterns. (ersjournals.com)
- Stratified multivariable linear regression explored the associations of these health determinants with premature mortality for high- and low-income groups. (cdc.gov)
Appendix1
- An appendix to the main report of the review of the Scottish Welfare Fund, containing technical detail of the secondary analysis. (gov.scot)
Linear2
- Quantile Regression as introduced by Koenker and Bassett (1978) seeks to complement classical linear regression analysis. (wikibooks.org)
- PLS discriminant analysis offers an interesting alternative to classical linear discriminant analysis. (xlstat.com)
Consumption1
- Exceptions to this can be found in the analysis of consumption functions which cover the whole consumption pattern (e.g. (acrwebsite.org)
Variable3
- This suggests that the second component can be used as an explanatory variable for predicting EC. (scirp.org)
- Household income is the main explanatory variable, with household- and individual-level controls. (biomedcentral.com)
- The main explanatory variable was body mass index (BMI) assessed at baseline. (medscape.com)
Associations1
- Paper II examined associations between study environment and exposure to sexual harassment using logistic regression and synergy indexes. (lu.se)
Factors6
- Some commonly stated explanatory factors such as delayed transfers of care showed limited evidence of being related. (bmj.com)
- Cox regression analyses were used to examine the impact of individual and socio-structural factors on incidence of crystal methamphetamine injection and suicidality, and assessed the independent effect of naturalistic psychedelic use on suicidality. (ubc.ca)
- The group regression method is used to test the impact of production factors on R&D. Whether input and corporate performance have a moderating effect, and the specific moderating and lagging effects of production factors are investigated. (hindawi.com)
- Analysis of other factors that impact on chances of a successful grant generally suggest that level of vulnerability is key, and that grants do appear to be targeted towards those with more recorded vulnerabilities. (gov.scot)
- Analysis of the key drivers of successful outcomes, based on regression analysis, which allows us to consider which factors drive outcomes more than others. (gov.scot)
- The analyses did not account for BMI changes that may have occurred during follow-up, fitness (either at baseline or during follow-up), differences in pharmacotherapies, or other key risk factors such as cholesterol levels. (medscape.com)
Qualitative1
- As for the qualitative phase of the study, semi-structured interviews conducted with more and less frequent strategy users, were analyzed by means of descriptive analysis. (ed.gov)
Findings1
- The findings of this study suggest that the selected proxies, dividend growth, earnings per share, and beta exhibit weak explanatory power in predicting returns of large U.K. companies. (ccsenet.org)
Assess1
- They will also be expected to be able to read and assess the analyses of others. (lu.se)
Exhibit1
- The analysis reveals that all 28 NWS cities exhibit a persistent UHI in summer and winter. (nersc.no)
Dataset1
- This dataset includes U.S. Geological Survey (USGS) flood-frequency analysis software PeakFQ input and output files for 299 streamgages in Wisconsin. (usgs.gov)
Simple1
- The most common approach is to rely on simple regression analysis based on household budget surveys and welfare aggregates used to measure poverty. (worldbank.org)
Power1
- Additional explanatory power-at least in summer-is provided by the surrounding background temperatures, which themselves are strongly correlated with latitude. (nersc.no)
Enables1
- Quantile Regression goes beyond this and enables one to pose such a question at any quantile of the conditional distribution function. (wikibooks.org)
Found1
- The LST analysis found differences in summer and winter regarding the UHI effect, and supports the hypothesis of seasonal differences in the causes of UHI formation. (nersc.no)
Identification1
- An anthropometric analysis was conducted for identification of nutritional risk. (bvsalud.org)
Characteristics1
- The greatest reduction in SEP for the peak-streamflow regional-regression equations was observed when additional new basin characteristics were included in the peak-streamflow regional-regression equations and when eastern Colorado was divided into two separate hydrologic regions. (usgs.gov)
Relationship1
- Through various statistical analyses, we attempted to determine the relationship between periodontal disease and halitosis. (nature.com)
Theory1
- In proof theory they offer a deep analysis of structural rules, demystifying some of their properties, and putting them into context. (ne.jp)
Exposure1
- Among 52 patients included in the analysis, 14 (27%) had a known exposure to a person with mpox, including sexual activity and other close intimate contact (eight) and household contact (six). (cdc.gov)
Outcomes1
- A comprehensive analysis of the costs and outcomes of cascade services is needed to help allocate and prioritize resources to achieve UNAIDS targets. (cdc.gov)