Statistical logistic models. Medical search. Frequent questions

In logistic regression analysis, there is no agreed upon analogous measure, but there are several competing measures each with limitations. (wikipedia.org)
In multiple logistic regression analysis adjusted for age, sex, diseases, and behavioural variables, the SRRST score was independently associated with history of falls and fractures. (springer.com)
A logistic regression analysis model was used after univariety analysis. (bvsalud.org)
Logistic regression analysis revealed that the untrained birth attendants was significantly higher in the tetanus group than the control group (OR=61.39, 95% CI 1.60, 354.33). (who.int)

Applied Logistic Regression (2nd ed. (wikipedia.org)

Descriptive statistical analyses and multivariate logistic regression modeling were conducted. (who.int)
Using pooled data from the 2001-2002 and 2013-2014 Medical Expenditure Panel Survey for each definition, this study conducted in 2017 used multivariate logistic regression to estimate changes in preventive dental care use among children from low-income families by race/ethnicity. (cdc.gov)

This introductory course is for SAS users who perform statistical analyses using SAS/STAT ® software. (sas.com)
Statistical analyses included split plot analyses of covariance and binary logistic regression (generalized linear models). (bepress.com)
Logistic regression analyses among never smoking children, adjusted for school-level clustering, examined associations of smoking norms with e-cigarette use, and of e-cigarette use with intentions to smoke tobacco within the next 2 years. (bmj.com)
The course will teach you how to conduct statistical analyses using a statistical package (SPSS or R). (manchester.ac.uk)
Students will develop their analytical skills by learning how to conduct statistical analyses using a statistical package and how to interpret the results of their analysis. (manchester.ac.uk)
Statistical analyses were done by Mann-Whitney U, 2 and logistic regression tests using Stata version 14. (who.int)

The logistic model of a mental test was introduced by the present writer in Chapters 17 through 20 of Lord and Novick, Statistical Theories of Mental Test Scores, where statistical inference methods were developed without assumption of a prior distribution of ability. (ets.org)
Such a distribution is assumed in this paper, and corresponding statistical inference methods and distribution theory are developed. (ets.org)
Algorithms of this nature use statistical inference to find the best class for a given instance. (wikipedia.org)
Demonstrate the use of methods for statistical inference. (manchester.ac.uk)

Preparing inputs for predictive models. (sas.com)
20% - Prepare inputs for predictive model performance. (sas.com)
This course covers predictive modeling using SAS/STAT ® software with emphasis on the LOGISTIC procedure. (sas.com)
a model's usefulness should not be judged on whether it is nominally true or false, but on its explanatory and predictive powers as compared with competing alternative models. (biorxiv.org)
R 2 , max‐rescaled R 2 , the Somers' D , and the concordance index c , shows that the revised model has better predictive abilities than the original model. (emerald.com)
Much of the chapter is devoted to linear and logistic regression - certainly the most widely used predictive modeling techniques. (oreilly.com)

When included in a multivariable model, older age, slower run times on ini-tial fitness tests, and prior nonspecific injury were associated with both any injury and specifically lower extremity MSK injury. (health.mil)
Multivariable logistic regression was employed to identify independent socioeconomic factors associated with low tuberculosis knowledge. (hindawi.com)
Using a multivariable Cox model with inverse probability weighting, we compared relevant outcomes between patients treated with early corticosteroids (before or within the first 48 h of ICU admission) with those who did not receive early corticosteroids (delayed group) or any corticosteroids at all (never group). (unav.edu)

The chapter begins by describing how even simple, descriptive statistics can be viewed as models. (oreilly.com)

These findings suggest that the basic E/I imbalance model should be updated to higher-dimensional models that can better capture the multidimensional computational functions of neural circuits. (biorxiv.org)
Statistical analysis of data is a key part of research and many research findings and recommendations are based on the results of statistical analysis. (manchester.ac.uk)
This could include conducting quantitative research, interpreting the findings of quantitative research studies or applying statistical thinking to public health practice. (manchester.ac.uk)

analysis of variance (ANOVA) · regression models: simple linear regression, multivariate linear regression and logistic regression. (lu.se)

[1] Results from probability theory and statistical theory are employed to guide the practice. (wikipedia.org)

Naïve Bayesian models are a very useful generalization of table lookup models that allow many more inputs than can usually be accommodated as dimensions of a lookup table. (oreilly.com)
The inputs to this model were factors output from a commercial patent database. (lesi.org)

Does it always help to adjust for misclassification of a binary outcome in logistic regression? (cdc.gov)

Here we combined computational simulations with analysis of in vivo 2-photon Ca 2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. (biorxiv.org)

The course can be seen as a tutorial in using a statistical analysis package (SPSS or R) and includes demonstrations of how to carry out statistical tests in these packages. (manchester.ac.uk)
Written assignment (statistical analysis of data set). (manchester.ac.uk)
We conducted cross-sectional analysis of EHR data collected in 2013 from 12,214 adult patients by using logistic regression. (cdc.gov)
However, this analysis, being explicitly tied to damages, is perhaps more closely tied to individual patents' economic value than the analysis presented in section IV.A. In section IV.B we looked for statistically different values of the factors that were the input to the model, comparing awarded high damages with the patents that were not litigated. (lesi.org)
Statistical analysis was realized using the Chi-square Test, ROC curve, Fisher Test and Mann-Whitney. (bvsalud.org)
This model acts as a starting point for a deeper analysis of consumer and producer behaviour. (lu.se)
Statistic analysis was carried out with SPSS 14.0 software. (who.int)
Statistical analysis was accomplished using Chi-squares test and Logistic Linear Regression. (bvsalud.org)

It is well known that in logistic regression, where the outcome is measured with error, a biased estimate of the association between the outcome and a risk factor may result if no proper adjustment is made. (cdc.gov)
In statistics , quality assurance , and survey methodology , sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. (wikipedia.org)
2/ 4 · demonstrate the ability to construct, estimate, and understand a regression model, and · demonstrate the ability to implement the points above using a statistical software. (lu.se)

In statistics , where classification is often done with logistic regression or a similar procedure, the properties of observations are termed explanatory variables (or independent variables , regressors, etc.), and the categories to be predicted are known as outcomes, which are considered to be possible values of the dependent variable . (wikipedia.org)

For passing the course the student shall · demonstrate knowledge about fundamental statistical concepts such as hypothesis testing, p-value, regression and confidence interval, and · demonstrate knowledge about how to apply statistical software for evaluating the concepts above. (lu.se)

Pseudo-R-squared values are used when the outcome variable is nominal or ordinal such that the coefficient of determination R2 cannot be applied as a measure for goodness of fit and when a likelihood function is used to fit a model. (wikipedia.org)

Model based on GA and DNN for prediction of mRNA-Smad7 expression regulated by miRNAs in breast cancer. (cancerindex.org)
The goodness‐of‐fit and prediction ability of the revised logistic regression model are more appropriate than those of the original model. (emerald.com)

Early work on statistical classification was undertaken by Fisher , [1] [2] in the context of two-group problems, leading to Fisher's linear discriminant function as the rule for assigning a group to a new observation. (wikipedia.org)
The company uses XGBoost and logistic regression models, so it is wise to use these to answer the nyc-13 classification question. (glassdoor.com)

We observed no statistical significant differences in any of the background variable between IG and CG. (egms.de)

However, it is unclear whether this onedimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. (biorxiv.org)
Construct and interpret multiple regression models and logistic regression models demonstrating an understanding of confounding. (manchester.ac.uk)
To assess non-response bias we modelled the propensity to participate at t3 (multiple logistic regression). (egms.de)

We calculated mean Scores for COHEP and heiQ at T0 and tested statistical significance with the T-Test for unpaired samples. (egms.de)
Statistical significance associations were found between stress and scholar difficulties, socioeconomic class C2 and D (p = 0,013) and asthma symptoms in a period less than or equal to 7 years (p = 0,003). (bvsalud.org)
There was no statistical significance association between asthma gravity and stress. (bvsalud.org)

Linear and logistic regression. (sas.com)
In the case of linear quadrupole ion trap (LTQ) or LTQ-FTICR LC/MS data, our logistic spectral model outperformed both XCorr (242% more peptides identified on average) and the X!Tandem E-value (87% more peptides identified on average) at a 1% false discovery rate estimated by decoy database approach. (nih.gov)
Generalized linear models and extensions. (wikipedia.org)

Donor strain colonization and recipient strain resilience were mostly independent of clinical outcomes, but accurately predictable using LASSO-regularized regression models that accounted for host, microbiome and procedural variables. (nature.com)
Improvements were recorded for each of the main participant groups in line with the expected outcomes in the logic model. (edu.au)

To pass the course the student shall · demonstrate the ability to make assessments with regard to relevant statistical and ethical aspects. (lu.se)

CHSD researchers received funding to evaluate the Illawarra Aboriginal Medical Service (IAMS) Safe Homes Safe Kids program, a home visiting model of early intervention as an injury prevention program for Aboriginal children aged 0-5 and their families. (edu.au)

A systematic approach and a clear model of development are needed to tailor physical activity interventions to the special needs of rural men. (cdc.gov)
This study aims to apply a systematic statistical approach, including several plot indexes, to diagnose the goodness of fit of a logistic regression model, and then to detect the outliers and influential observations of the data from experimental data. (emerald.com)

Allison, Paul D. "Measures of fit for logistic regression" (PDF). (wikipedia.org)

Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. (nih.gov)
Each variable was modeled using logistic regression to determine its impact on subsequent injury risk. (frontiersin.org)
A suitable logistic regression model in which the relationship between the response variable and the explanatory variables is found. (emerald.com)

This course aims to provide the student with basic statistical literacy, the ability to understand statistics. (manchester.ac.uk)
An awareness of statistical methods and the ability to interpret data from published studies is important for a career in public health. (manchester.ac.uk)

The C statistic is a commonly reported measure of screening test performance. (nih.gov)

25% - Measure model performance. (sas.com)
We designed a patent evaluation method based on statistical methods to create a single-dimensioned measure of a single patent's value. (lesi.org)

Successful statistical practice is based on focused problem definition. (wikipedia.org)
Apply statistical thinking when conducting or reviewing research in professional practice. (manchester.ac.uk)
The participating hospitals represent varied models of service delivery, and there is a potential to learn from best practice in different healthcare systems. (bmj.com)

Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. (nih.gov)
We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. (nih.gov)

Students will develop problem solving skills through developing their skills in statistical thinking. (manchester.ac.uk)

Here, we introduce the peptide validation software component of this system, which combines relational database-integrated electronic manual spectral annotation in Java with a new software tool in the R programming language for the generation of logistic regression spectral models from user-supplied validated data sets and flexible application of these user-generated models in automated proteomic workflows. (nih.gov)
The second part is implementation of the first part using statistical software. (lu.se)
The computer sessions will deal with the usage of statistical software. (lu.se)

As discussed below, we developed a model predicting the likelihood that a patent would be selected for litigation. (lesi.org)
Further, and separate from our regression model, we compared the effect of the claimed technology on the likelihood that a patent would be asserted in litigation. (lesi.org)

PS: since this is a school project, it is the project requirement that we must use factor model. (glassdoor.com)

After three outliers and influential observations (cases 11, 27, and 49) are removed from the data, and the remaining observations are refitted the goodness‐of‐fit of the revised model to the data is improved. (emerald.com)

The pricing problem is developed within a model of supply and demand. (lu.se)

Describe a time you helped develop a statistical model at work or on a school project. (glassdoor.com)

A program logic model and evaluation framework was developed in collaboration with the IAMS Aboriginal family workers. (edu.au)
Clients expressed a high degree of satisfaction with the family workers' delivery of the program and the holistic model of service provision offered by the IAMS. (edu.au)

Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. (nih.gov)

These associations remained after logistic regression model. (bvsalud.org)

Logistic regression will always be heteroscedastic - the error variances differ for each value of the predicted score. (wikipedia.org)
Therefore, it is inappropriate to think of R2 as a proportionate reduction in error in a universal sense in logistic regression. (wikipedia.org)

Diseases5

Chemicals and Drugs1

Analytical, Diagnostic and Therapeutic Techniques and Equipment44

Psychiatry and Psychology3

Phenomena and Processes14

Disciplines and Occupations2

Anthropology, Education, Sociology and Social Phenomena2

Technology, Industry, Agriculture1

Information Science8

Named Groups4

Health Care48

Geographicals6

Regression analysis4

Applied Logistic Regression1

Multivariate logistic regression2

Analyses6

Inference4

Predictive6

Multivariable3

Descriptive1

Findings3

ANOVA1

Results1

Inputs2

Binary1

Theory1

Analysis8

Estimate3

Procedure1

Hypothesis1

Outcome1

Prediction2

Classification2

Differences1

Multiple3

Significance3

Linear3

Outcomes2

Demonstrate1

Evaluate1

Systematic2

Measures1

Variable3

Ability2

Test1

Measure2

Practice3

Methods2

Skills1

Software3

Likelihood2

Requirement1

Observations1

Problem1

Describe1

Workers2

Similar1

Associations1

Error2