Multiple Tables Sweave/Latex - Stack Overflow

Multiple Tables Sweave/Latex - Stack Overflow: "Multiple Tables Sweave/Latex"

Obesity - Which Obesity Indicators Are Better Predictors of Metabolic Risk[quest]: Healthy Twin Study

Obesity - Which Obesity Indicators Are Better Predictors of Metabolic Risk[quest]: Healthy Twin Study: "Which Obesity Indicators Are Better Predictors of Metabolic Risk?: Healthy Twin Study"

spss

medcalc for comparing pairs of AUC ROC

blog on blogging GO DOWN

http://www.bloggodown.com/2010/01/25-super-firefox-addons-for-bloggers.html

https://addons.mozilla.org/en-US/firefox/addon/1730/

Regression Statistical Procedure

Regression Statistical Procedure: "ROC (Receiver Operating Characteristics) Curve is useful for evaluating and comparing the performance of classification models where the response variable is binary."

ROC curve comparison, software, statistics etc.

1. SPSS can draw line (also multiple lines for several predictors), can compute SE, 95%CI (nonparametric method), but cannot!!!! compare AUC ROC for two predictors with statistical test, (difference or lack of it can be deduced from overlap of 95%CI for the predictors beng compared, but no formal test, NO p-value!!!!).

2. methods for doing this - comparing AUC ROC of two curves (predictors), Delong 1988, Hanley 1982 ...., permutation/boostrapping CI ...

CF binormal distribution assumption.

SPSS - SE AUC ROC - two methods (options)
1. nonparametric,
2. - bi-negative exponential distribution????

*xxx* cf. Park et al 2004 Korean ..Journal - very nice intro, nonmath, but insightful what has to be done...., includes explanation on PARAMETRIC vs nonPARAMETRIC ROC estimation (smooth vs empirical), cf concept of partial AUC ROC
--- give nice and simple overview on assumptions, and when PARAMETRIC vs NONparametric methods should be used. (continuous, ordinal, skewed, sparse categories etc).


*xxx* more technical-but educational - SUGI .... tutorial on SAS macro that is able to compute p-value for difference between two AUC ROC, explaining different statistical approaches

more technical: SAS help on nonparametric comparison of two ROC curves.

the journal article reference and Rcode for three different methods of calculation of SE of AUC ROC. R forum -- (ref. Hajian-Tilaki, Hanley 2002?

Rcode for the DeLong method of AUC ROC SE estimation - nonparametric


ROCKIT by prof Metz from CHICAGO, free, downloaded, but IMHO will t ake some time to get around, to prepare input file, etc.

cf things with bootstraping, jacknifing etc, nonparametric tests.

- cf childhood predictors of young onset T2DM ... Franks et al. DIABETES 2007 = methods

CF comparison of 8 software packages for performing ROC analysis. (Stephan ClinChem 2003

medcalc by SCHOONJANS - commercial sw for cox hazard, ROC

Jane, Longton, Pepe 2009: Accommodating Covariates in ROC Analysis


ROC EXPLANATION

from Park 2004. cf Lyssenko, Meigs 2008 NEJM

One of the most popular measures is the area under
the ROC curve (AUC) (1, 2). AUC is a combined measure
of sensitivity and specificity. AUC is a measure of the
overall performance of a diagnostic test and is interpreted
as the average value of sensitivity for all possible values of
specificity (1, 2). It can take on any value between 0 and 1,
since both the x and y axes have values ranging from 0 to
1. The closer AUC is to 1, the better the overall diagnostic
performance of the test, and a test with an AUC value of 1
is one that is perfectly accurate (Fig. 2). The practical lower
limit for the AUC of a diagnostic test is 0.5. The line
segment from 0, 0 to 1, 1 has an area of 0.5 (Fig. 2). If we
were to rely on pure chance to distinguish those subjects
with versus those without a particular disease, the resulting
ROC curve would fall along this diagonal line, which is
referred to as the chance diagonal (Fig. 2) (1, 2). A diagnos-

cf values of test from 0.5 (random guess) to 1 (perfect predictor).

Comparison of data analysis packages: R, Matlab, SciPy, Excel, SAS, SPSS, Stata - Brendan O'Connor's Blog

Comparison of data analysis packages: R, Matlab, SciPy, Excel, SAS, SPSS, Stata - Brendan O'Connor's Blog: "Comparison of data analysis packages: R, Matlab, SciPy, Excel, SAS, SPSS, Stata"

Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists

Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists: "Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists"

Plot ROC curve and lift chart in R « Heuristic Andrew

Plot ROC curve and lift chart in R « Heuristic Andrew: "If this programming is too much for you, try rattle (a GUI interface to R for data mining) or Weka (a machine learning suite). Otherwise, go on to the next tutorial: Compare performance of machine learning classifiers in R."

"[R] ROC curve from logistic regression"

"[R] ROC curve from logistic regression"

ROC curve comparison

methods

parametric, nonparametric

deLong, Hanley ... references included in reference.

SPSSX-L archives -- December 1999 (#254)

SPSSX-L archives -- December 1999 (#254): "Re: Meaning of ROC Curves: was Logistic Regression"

ROCKIT compare ROC AUC

Software_index: "ROCKIT also calculates the statistical significance of differences between ROC index estimates and parameters. On the basis of a 'bivariate binormal' model, it allows for comparison of 2 paired, partially paired, or unpaired datasets (which would represent, for example, different imaging modalities or diagnostic tests) with regard to:
Differences in the binormal ROC curve parameters a and b (related to the difference in the mean and of the standard deviations of the two latest normal distributions used in the fit)
Difference in the areas (Az) under the two estimated binormal ROC curves"

ROC curves comparison - comp.soft-sys.stat.spss | Google Groups

ROC curves comparison - comp.soft-sys.stat.spss Google Groups: "How can I compare two (or more) ROC curves to see if at least one of
> them is significantly different compared to the others ? I know how to
> draw a ROC curve in SPSS 15 but I do not know how to compare two
> curves to highlight significant (or insignificant) difference, by p-
> value."

MDACC Bioinfo:Public Data

MDACC Bioinfo:Public Data: "Publicly Available Data"

OpenClinica User Manual/FindingOIDs - Wikibooks, collection of open-content textbooks

OpenClinica User Manual/FindingOIDs - Wikibooks, collection of open-content textbooks: "OpenClinica User Manual/FindingOIDs"

XML EDITOR FREE - SERNA
BY SYSTEX -- CF PLONE CMS, ZOPE ???

About Texy | Texy

About Texy Texy: "About Texy"

stratified analysis, epidemiology

Rothman epidemiologybook

stratified analysis
by greenland sander.

googlebooks.

http://books.google.sk/books?id=Z3vjT9ALxHUC&pg=PA283&lpg=PA283&dq=interaction+versus+stratified+analysis&source=bl&ots=aOMKdIWH9T&sig=BvQKFnUsjzqtUO4hMImdFX0o4cQ&hl=sk&ei=RpUoTOGbNISWONSypasC&sa=X&oi=book_result&ct=result&resnum=7&ved=0CEIQ6AEwBg#v=onepage&q=interaction%20versus%20stratified%20analysis&f=false

Personalized medicine and genomics: challenges and... [Med Decis Making. 2010 May-Jun] - PubMed result

Personalized medicine and genomics: challenges and... [Med Decis Making. 2010 May-Jun] - PubMed result: "Personalized medicine and genomics: challenges and opportunities in assessing effectiveness, cost-effectiveness, and future research priorities"

R Data Analysis Examples: Logit Regression

R Data Analysis Examples: Logit Regression: "R Data Analysis Examples
Logit Regression"

centering variables

link to google books

http://books.google.sk/books?id=VtU3-y7LaLYC&pg=PA67&lpg=PA67&dq=centering+log+transformed+variables&source=bl&ots=cxvr4vpkkG&sig=A9C67EqnIkg34i_zKRiPOxdRGxI&hl=sk&ei=M4I5TKn5BMqmOI2L7YoK&sa=X&oi=book_result&ct=result&resnum=7&ved=0CD8Q6AEwBjgK#v=onepage&q=centering%20log%20transformed%20variables&f=true

Experimental design and data analysis for biologists Od autorov: Gerald Peter Quinn,Michael J. Keough

test for trend

test for trend: "How do I perform a test for linear trend of a variable that is coded as
a dummy variable in a logistic regression analysis?"

Epidemiologic Perspectives & Innovations | Full text | Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies

Epidemiologic Perspectives & Innovations Full text Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies: "Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies"

R - Generalized linear Models

R - Generalized linear Models: "5 Generalized Linear Models"

Comparison of GE Centricity electronic medical rec... [Popul Health Manag. 2010] - PubMed result

Comparison of GE Centricity electronic medical rec... [Popul Health Manag. 2010] - PubMed result: "Comparison of GE Centricity electronic medical record database and national ambulatory medical care survey findings on the prevalence of major conditions in the United States."

Information resources for epidemiologists: Textbooks

Information resources for epidemiologists: Textbooks: "Information resources for epidemiologists - textbooks and other books"

SPSS syntax to change string into numeric variable and vice versa, including a decimal or comma separator

SPSS syntax to change string into numeric variable and vice versa, including a decimal or comma separator: "Problem Subject: SPSS syntax to change string into numeric variable and vice versa, including a decimal or comma separator"

Applications, programs and R statistical functions for epidemiology

Applications, programs and R statistical functions for epidemiology: "Applications, programs and R statistical functions for epidemiology"

Search Results for INTERPRETING GRAPH DATA.ppt - Download Free Microsoft Powerpoint Documents - ZxDrive.com

Search Results for INTERPRETING GRAPH DATA.ppt - Download Free Microsoft Powerpoint Documents - ZxDrive.com

IAS Literature e-Newsletter: June 2010

IAS Literature e-Newsletter: June 2010: "International Atherosclerosis
Society Literature e-Newsletter
JUNE 2010"

Association between increasing levels of hemoglobi... [Coron Artery Dis. 2010] - PubMed result

Association between increasing levels of hemoglobi... [Coron Artery Dis. 2010] - PubMed result: "Association between increasing levels of hemoglobin A1c and coronary atherosclerosis in asymptomatic individuals without diabetes mellitus."

QMSS e-Lessons | Introduction

QMSS e-Lessons Introduction: "Welcome to the Quantitative Method in the Social Sciences e-lessons."

Čo všetko musíte voziť vo svojom aute - Pravda.sk

Čo všetko musíte voziť vo svojom aute - Pravda.sk: "Čo všetko musíte voziť vo svojom aute
Tomáš Andrejčák 15. júla 2010 8:47"

CENTERING VARIABLES REFS Linear Mixed Models: Statnotes, from North Carolina State University, Public Administration Program

Mean-Centering Does Not Alleviate Collinearity Problems in Moderated Multiple Regression Models


centering variables - collinearity in interaction terms, SAS, animation, demo

Linear Mixed Models: Statnotes, from North Carolina State University, Public Administration Program: "Centering. It is customary to center data prior to running LMM or HLM. Centering means subtracting the mean, so means become zero. Two main types of centering are group mean centering and grand mean centering. For instance, in a study of PerformanceScore, there might be a PerformanceIndividualScore at level 1 and a PerformanceAgencyScore at level 2, where the latter was a mean score for all employees in an agency. The researcher might center PerformanceIndividualScore for individuals by centering on their group (agency) means, where groups were agencies, on the theory that group performance influenced individual performance and differences from the group means should therefore be the variable of interest. Or one could center each PerformanceIndividualScore on the grand mean of all such scores across agencies. Grand mean centering is preferred over group mean centering unless there is theoretical justification for the latter."

Grand mean centering often improves the interpretability of coefficients because "0" now has a meaning (ex., 0 income is mean income, whereas before centering, 0 income might be out of the range of actual observations). Group mean centering, in contrast, changes the meaning of coefficients in complex ways which make coefficients hard to interpret, as different mean values are subtracted from different sets of raw scores. As a result, with group mean centering it is not possible to recalculate output back to raw score interpretations. In essence, one is dealing with a different variable after group mean centering. Grand mean centered income, for instance, will yield different slopes but the same deviance and residual errors as uncentered raw data. Group mean centered income does not. Group mean centered income is no longer simple income but rather measures income deviation from group means. The researcher must examine his or her theoretical model and decide if that is really what was wanted for the "income" variable. As noted by Kreft, de Leeuw, and Aiken (1995), the choice of centering must be made on a theoretical rather than statistical basis, and "centering around the group mean amounts to fitting a different model from that obtained by centering around the grand mean or by using raw scores" (p. 1). Most LMM/HLM software packages support various types of automatic centering. Centering considerations are further discussed in Burton (1993) and Hoffman & Gavin (1998).

Statistics Papers for Download

Statistics Papers for Download: "Statistics Papers for Download"

SPSS Library: Understanding contrasts

SPSS Library: Understanding contrasts: "WHAT KIND OF CONTRASTS ARE THESE?

David P. Nichols"

Organize research, collaborate & discover new knowledge | Mendeley

Organize research, collaborate & discover new knowledge Mendeley: "Organize research, collaborate, and discover new knowledge"

cf zotero
endnote
reference manager

logistic regression, linear trend test for OR

cf linear trend test for crosstabulated data - cochran armittage, mantel haenzel, linear-by-linear association

in LOGISTIC REGRESSION

cf to test linear trend (of OR) across quartiles we entered 4-level ordinal term representing medians of 4 quartiles of original continuous

cf Ridker Comparison of CRP and LDL - NEJM

Nieto

Shahar - 2000

find:
*** *** ***
books with worked example how to compute trends in OR logistic regression models

"logistic regression linear trend test Odds ratio how to" Jewell
Nicholas Jewell Statistics for epidemiology. p222
google books

***
statnotes
http://faculty.chass.ncsu.edu/garson/PA765/logistic.htm#contrasts
***
- Maxwell & Delaney "Designing Experiments and Analyzing Data" Lawrence Erlbaum Associates
cf old nabble- SPSS discussion forum

If you want to know more on polynomial contrasts, check specialised books,
like: Maxwell & Delaney "Designing Experiments and Analyzing Data" Lawrence
Erlbaum Associates. If you Google a bit using this search key: "Polynomial
contrasts logistic regression", you will se that it is widely used in
experimental research to test for linear and non linear trends.

*** ***

- selvin , statistical analysis for epidemiologic data, p228 - cf stata-"trend test after logistic regression"

google books

XXX: trend test after logistic regression.

Re: st: trend test after logistic regression.: "trend test after logistic regression"

Linear versus logistic regression when the dependent variable is a dichotomy

SpringerLink - Journal Article: "Linear versus logistic regression when the dependent variable is a dichotomy"

Choosing Statistical and Epidemiologic Methods

Choosing Statistical and Epidemiologic Methods: "Choosing a Statistical Method, with Automatic Internet Searching"

Choosing Statistical and Epidemiologic Methods

Choosing Statistical and Epidemiologic Methods: "Choosing a Statistical Method, with Automatic Internet Searching"

Improving the Presentation of Results of Logistic Regression

bulletin86_1: "Improving the Presentation of Results of Logistic Regression
with R"

Epidemiologic Perspectives & Innovations | Full text | Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies

Epidemiologic Perspectives & Innovations Full text Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies: "Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies
Ludwig A Hothorn"

Linear Trend Tests of ORs

RE: SV: Re: SV: RE: Re: st: Linear Trend Tests of ORs: "Linear Trend Tests of ORs"

Trend Tests in Epidemiology: P-Values or Confidence Intervals?. Ludwig A. Hothorn. 1999; Biometrical Journal - Wiley InterScience

Trend Tests in Epidemiology: P-Values or Confidence Intervals?. Ludwig A. Hothorn. 1999; Biometrical Journal - Wiley InterScience: "Trend Tests in Epidemiology: P-Values or Confidence Intervals?
Ludwig A. Hothorn, Prof. Dr."

Computer Code Table

Computer Code Table: "Index to computer programs"

Logistic regression

Logistic regression: "Logistic regression"

logistic regression, model fit, trend test, boook

Nicholas P. Jewell, "Statistics for Epidemiology" Chapman. xxxxxxxx



Hosmer DW, Jr, Lemeshow S. Applied logistic regression 1989:25-37 John Wiley & Sons New York. .

In all analyses, we modeled Lp(a) concentrations as quartiles to avoid the
assumption of linearity and to reduce the effects of outliers. Furthermore, we
used median Lp(a) concentrations for the categories to test for linear trends
across quartiles. We categorized the data according to the 90th, 95th, and 99th
percentiles and performed threshold analyses. We also used the test of Hosmer
and Lemeshow to evaluate the goodness of fit of the data to the models (20).

Clinical Chemistry. 2008;54:285-291.)

interaction, HOW TO , REGRESSION, XXX

http://core.ecu.edu/psyc/wuenschk/MV/MultReg/Regr-SeqMod.doc

Sequential Moderated Multiple Regression AnalysisÓ

Continuous Moderator Variables in Multiple Regression
http://core.ecu.edu/psyc/wuenschk/MV/multReg/Moderator.doc

PGS 101-INTRODUCTION TO PSYCHOLOGY

PGS 101-INTRODUCTION TO PSYCHOLOGY: "Readings in Hierarchical Linear Modeling"

learning and training Multilevel Modelling online course"

learning and training: "Multilevel Modelling online course"

interaction effects centering variables

Regression: Statnotes, from North Carolina State University, Public Administration Program: "Interaction effects are sometimes called moderator effects"

how to perform likelihood ratio test in SPSS - Hľadať v Google

how to perform likelihood ratio test in SPSS - Hľadať v Google: "Multivariate Data Analysis Using SPSS"

How to Use SPSS for Contingency Table, Relative Risk, Odds Ratio ...

How to Use SPSS for Contingency Table, Relative Risk, Odds Ratio ...

how to perform likelihood ratio test in SPSS - Hľadať v Google

how to perform likelihood ratio test in SPSS - Hľadať v Google: "More on Model Fit and Significance of Predictors with Logistic ... - 7:40 - [ Preložiť túto stránku ]
Formát súboru: Microsoft Word - HTML verzia
This is one use of the likelihood ratio test between two nested models (referrred to as “chi-square” in the SPSS logistic output). ...
www.upa.pdx.edu/IOA/newsom/da2/ho_logistic3.doc - Podobné"

An Introduction to Logistic Regression

An Introduction to Logistic Regression

by whitehead

Annotated SPSS Output: Logistic Regression

Annotated SPSS Output: Logistic Regression: "Annotated SPSS Output
Logistic Regression"

SPSS Code Fragments: A few SPSS loops for renaming variables dynamically

SPSS Code Fragments: A few SPSS loops for renaming variables dynamically: "A few SPSS loops for renaming variables dynamically"

SPSS Code Fragment: Graphing results in logistic regression

SPSS Code Fragment: Graphing results in logistic regression: "SPSS Code Fragment
Graphing results in logistic regression"

logistic regression, interaction CHASS - statnotes

Can I create interaction terms in my logistic model, as with OLS regression?
Yes. As in OLS regression, interaction terms are constructed as crossproducts of the two interacting variables.

How are interaction effects handled in logistic regression?
The same as in OLS regression. One must add interaction terms to the model as crossproducts of the standardized independents and/or dummy independents. Some computer programs will allow the researcher to specify the pairs of interacting variables and will do all the computation automatically. In SPSS, use the categorical covariates option: highlight two variables, then click on the button that shows >a*b> to put them in the Covariates box .The significance of an interaction effect is the same as for any other variable, except in the case of a set of dummy variables representing a single ordinal variable.
When an ordinal variable has been entered as a set of dummy variables, the interaction of another variable with the ordinal variable will involve multiple interaction terms. In this case the significance of the interaction of the two variables is the significance of the change of R-square of the equation with the interaction terms and the equation without the set of terms associated with the ordinal variable. (See the StatNotes section on "Regression" for computing the significance of the difference of two R-squares).


ASSUMPTIONS:
Centered variables. As in OLS regression, centering may be necessary either to reduce multicollinearity or to make interpretation of coefficients meaningful. Centering is almost alway recommended for independent variables which are components of interaction terms in a logistic model. See the full discussion in the section on OLS regression, here.

COLLINEARITY
Is multicollinearity a problem for logistic regression the way it is for multiple linear regression?
Absolutely. The discussion in "Statnotes" under the "Regression" topic is relevant to logistic regression.

What is the logistic equivalent to the VIF test for multicollinearity in OLS regression? Can odds ratios be used?
Multicollinearity is a problem when high in either logistic or OLS regression because in either case standard errors of the b coefficients will be high and interpretations of the relative importance of the independent variables will be unreliable. In an OLS regression context, recall that VIF is the reciprocal of tolerance, which is 1 - R-squared. When there is high multicollinearity, R-squared will be high also, so tolerance will be low, and thus VIF will be high. When VIF is high, the b and beta weights are unreliable and subject to misinterpretation. For typical social science research, multicollinearity is considered not a problem if VIF <= 4, a level which corresponds to doubling the standard error of the b coefficient. As there is no direct counterpart to R-squared in logistic regression, VIF cannot be computed -- though obviously one could apply the same logic to various psuedo-R-squared measures. Unfortunately, I am not aware of a VIF-type test for logistic regression, and I would think that the same obstacles would exist as for creating a true equivalent to OLS R-squared. A high odds ratio would not be evidence of multicollinearity in itself. To the extent that one independent is linearly or nonlinearly related to another independent, multicollinearity could be a problem in logistic regression since, unlike OLS regression, logistic regression does not assume linearity of relationship among independents. Some authors use the VIF test in OLS regression to screen for multicollinearity in logistic regression if nonlinearity is ruled out. In an OLS regression context, nonlinearity exists when eta-square is significantly higher than R-square. In a logistic regression context, the Box-Tidwell transformation and orthogonal polynomial contrasts are ways of testing linearity among the independents.

tabachnick fidell - eBook Downloads

tabachnick fidell - eBook Downloads: "An Introduction to Logistic Regression Analysis and Reporting
Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins. Tabachnick, B. G., & Fidell, L. S. (2001).
bit.csc.lsu.edu/~jianhua/emrah.pdf - View"

Regression Models for Count Data: Illustrations using Longitudinal Predictors of Childhood Injury -- Karazsia and van Dulmen 33 (10): 1076 -- Journal of Pediatric Psychology

Regression Models for Count Data: Illustrations using Longitudinal Predictors of Childhood Injury -- Karazsia and van Dulmen 33 (10): 1076 -- Journal of Pediatric Psychology: "Regression Models for Count Data: Illustrations using Longitudinal Predictors of Childhood Injury*"

logistic regression interaction testing how to - Hľadať v Google

logistic regression interaction testing how to - Hľadať v Google: "Testing and Interpreting Mediational and Moderational Models in ... - [ Preložiť túto stránku ]
Formát súboru: Microsoft Powerpoint - HTML verzia
Testing interactions in logistic regression is similar to OLS regression methods, in that one includes an interaction term in the model predicting a binary ..."

King: xxxx
http://faculty.washington.edu/kingkm/Logistic%20Regression/mediation%20in%20logistic.ppt

nonparametric logistic regression - Hľadať v Google

nonparametric logistic regression - Hľadať v Google: "Nonparametric simple regression: smoothing scatterplots - Výsledky kníh Google"

Statistics with R

Statistics with R: "using the statistical environment R"

FAQ: A comparison of different tests for trend

trend test in logistic regression ??? cf Nieto 2000 Sleep apnea health hypertension study

cf cochrane-armittage test for linear trend in genotypes (genetic association testing)

nice explanation - as how some statistical tests are something we now, but have new names. ...... at the same time a bit confusing.


FAQ: A comparison of different tests for trend: "Does Stata provide a test for trend?"

logistic regression resources

1. binary logistic regression - Rodriguez. Available at: http://data.princeton.edu/wws509/notes/c3.pdf [Cit Júl 3, 2010].

general statistical text, but on authors webpage u can find examples how to perform analysis in R statistical software. !!!!!

2. Categorical Data: Part 6: Logistic Regression. Available at: http://www.math.yorku.ca/SCS/Courses/grcat/grc6.html [Cit Júl 3, 2010]. / for SAS , but general concepts very intuitive //

3. log linear model - zrozumiteľné - Rodriguez. Available at: http://data.princeton.edu/wws509/notes/c5.pdf [Cit Júl 3, 2010].

1. linear models - rodriguez - zrozumiteľne! Available at: http://data.princeton.edu/wws509/notes/c2.pdf [Cit Júl 3, 2010].

generalized linear model, R

http://data.princeton.edu/R/glms.html

Odds ratio - Wikipedia, the free encyclopedia

Odds ratio - Wikipedia, the free encyclopedia: "Odds ratio"

FAQ: How do I interpret odds ratios in logistic regression?

FAQ: How do I interpret odds ratios in logistic regression?: "FAQ: How do I interpret odds ratios in logistic regression?"

Stata FAQ: How do I interpret odds ratios in logistic regression?

Stata FAQ: How do I interpret odds ratios in logistic regression?: "How do I interpret odds ratios in logistic regression?"