Comparing multiple proportions: The Marascuillo procedure
from NIST Handbook. includes syntax for calculation
BIOS nice overview of proportions / basics - equivalence of Pearson chi-square test and z-test
Macro from Minitab
This macro performs a multiple comparisons test on proportion data using # Tukey's honest significant difference test.
statistics for lawyers
google books
http://books.google.com/books?id=_bR9Q-EERlIC&pg=PA200&lpg=PA200&dq=comparing+multiple+proportions&source=bl&ots=PTb87Wa-gr&sig=PuEEGFcVwPlqSnhLUF6zXoXJ5p0&hl=en&sa=X&oi=book_result&resnum=5&ct=result#PPA201,M1
piatok 21. novembra 2008
pondelok 10. novembra 2008
utorok 7. októbra 2008
SEQUENCING low price, individual genome
Low-Price Mapping SEQUENCING
companies developing/offering genome sequencing
- COMPLETE GENOMICS - 5000 $ /Reid, Radoje Drmanac
- applied biosystems
- Knome - cca 20 customers
- cf Systems Biology Institute as customer for complete genomics
companies developing/offering genome sequencing
- COMPLETE GENOMICS - 5000 $ /Reid, Radoje Drmanac
- applied biosystems
- Knome - cca 20 customers
- cf Systems Biology Institute as customer for complete genomics
sobota 20. septembra 2008
datamining
datamining in genetic/genomic research
finland Helsinki
DM in LD mapping ... haplotype association etc. PDF
PUBLICATIONS BY HANNU TOIVONEN, UNI helsinki
finland Helsinki
DM in LD mapping ... haplotype association etc. PDF
PUBLICATIONS BY HANNU TOIVONEN, UNI helsinki
piatok 19. septembra 2008
štvrtok 18. septembra 2008
datamining intro
datamining course materials from Australian national Uni,
- same as links below.
COURSE SLIDES -FROM slideshare.com
- same as links below.
COURSE SLIDES -FROM slideshare.com
by prof Lanzi, some slides look identical to slides provided by ANU
- but generally looks good, COMPREHENSIBLE .....
DATAMINING, UNSUPERVISED RECORD LINKAGE.
Markus Hegland , australia
CHRISTEN
DATAMINING. CHALLENGES, MODELS, METHODS AND ALGORITHMS
year 2003
intro -- mainly from the standpoint of computation science.. algorithms
--
progream - FEBRL year 2008
Febrl - A Freely Available Record Linkage System with a Graphical User Interface Peter Christen Proceedings of the Australasian Workshop on Health Data and Knowledge Management (HDKM), Wollongong, January 2008.
- DISTANCE - EUCLIDEAN, PYTHAGOREAN ETC WOLFRAM MATH
ASSOCIATION RULES
- Support, confidence
Support gives total number of transaction of any particular item are occurring in datasets while confidence gives strength of a data in a dataset, we can say support is probability of A and B while confidence is conditional probability. Association rule based on these two characteristics.
pondelok 15. septembra 2008
c-statistic
____?????? I would like to know whether we can calculate C-statistic using SPSS >> 13.
> If by the "c-statisitc" you are referring to the measure of the > discriminative power of the logistic equation, you can calculate it by > saving the predictive probabilities from the logistic regression > analysis and running a ROC curve with the preditive probabilities as > the "test variable." The c-statistic is the area under the curve > value.
HTH
In R/S-Plus you can just use the lrm function in the Design package or:
mean.rank <- mean(rank(x)[y == 1]) c.index <- (mean.rank - (n1 + 1)/2)/(n - n1)
(where n1 is the number of observations with y=1)
or use the somers2 function in the Hmisc package.
(where n1 is the number of observations with y=1)
or use the somers2 function in the Hmisc package.
Frank Harrell
utorok 9. septembra 2008
statistics general
Q&A by Seaman /course in psychology/
Newsom Portland UNI - handouts to course , SPSS examples
STATNOTES - WEBLECTURES. brief, explanatory, with formulas and examples of both manual calculation of basic tests and examples in SPSS.
semipartial correlation coefficient = Rsq change,,,,, semipartial = part correlation
structural equation modelling BASICS - Newsom handout
Dr Newsom has nice disclaimer on his page : "DISCLAIMER: I am not always right."
nedeľa 7. septembra 2008
sobota 6. septembra 2008
genetics statistics microarray spss
Genovese
tutorial on false discovery rate - looks comprehensible
//also see the article by authors of the method FDR /method for controlling multiple comparison problem / benjamini, hochberg from 1995
Step-by-Step Tutorial for analyzing Affymetrix expression microarraysin the R statistical environment: HELPWITHSCHOOL.COM
SPSS tutorials at texas ..
latex /superscripts/
SPSS macro basics at Raynald
SPSS datenmanagement mit SPSS googlebooks
gene set enrichment analysis editorial
Rodenburg
A framework to identify physiological responses in microarray-based gene expression studies: selection and interpretation of biologically relevant genes
A Bayesian Measure of the Probability of False Discovery in Genetic Epidemiology Studies
Jon Wakefield*
Jon Wakefield*
Comprehensive Analysis of Affymetrix Exon Arrays Using BioConductor
Michał J. Okoniewski, Crispin J. Miller *
Michał J. Okoniewski, Crispin J. Miller *
streda 3. septembra 2008
SPSS statistics resources
flash/audiovisual tutorials with screenshots and narrated.
wide range of topics, including advanced ones like nonlinear, segmented, robust regression,
Box-Cox transformation, contour, surface plotting and much more....
*****************Uni TEXAS
utorok 2. septembra 2008
nedeľa 31. augusta 2008
problems SPSS/automation
using SPSS OMS in split file mode. how to add labels/subtypes to create file with tables from all subgroups of splitting variable.
macro - cf learn - check german site
sobota 30. augusta 2008
CRP cutoffs
review CRP in clinical practice on Medscape by Musunuru 08/2008
Laaksonen 2005 - C-reactive protein in the prediction of cardiovascular and overall mortality in middle-aged men: a population-based cohort study
Laaksonen 2005 - C-reactive protein in the prediction of cardiovascular and overall mortality in middle-aged men: a population-based cohort study
streda 27. augusta 2008
power and sample size programs
Biostatistics Uni UCSF
list of statistical programs for different types of analyses - extensive
on estimation of power/ss for logistic regression in stata from UCLA
site - but rather simple calculations //by eugene demidenko //cf author of recent book on Mixed models
site2 - logistic regression with covariate with measurement ERROR, generalized linear models etc - ALSO GIVES PLOTS OF POWER, OR, SAMPLE SIZE
list of statistical programs for different types of analyses - extensive
on estimation of power/ss for logistic regression in stata from UCLA
site - but rather simple calculations //by eugene demidenko //cf author of recent book on Mixed models
site2 - logistic regression with covariate with measurement ERROR, generalized linear models etc - ALSO GIVES PLOTS OF POWER, OR, SAMPLE SIZE
utorok 26. augusta 2008
reader genetics
Diabgen
Finland, Askenazi Jews, Pomerania Germans, English
rare SNP - value Gorlov 2007
power analysis for GWAS KLEIN 2008
exocrine pancreas reprogramming into betacells zhou 2008
Finland, Askenazi Jews, Pomerania Germans, English
rare SNP - value Gorlov 2007
power analysis for GWAS KLEIN 2008
exocrine pancreas reprogramming into betacells zhou 2008
ONLINE LEARNING
videolectures - biology, genetics, bioinformatics
eg.
http://videolectures.net/msht07_omont_gbba/
COMMENT: browsed videolectures.net yester and tried to watch cca 3 lectures on bioinformatics but the level of presentation was rather mediocre. topics interesting, but presented by some phd students in an uninteresting , hard-to-follow way.
but there is much more stuff, maybe i just didnt get representative sample, so hope to find something interesting.
OTHER SOURCE OF LECTURES/courses FROM MIT
opensource lectures from massachussets institute of technology.
eg.
http://videolectures.net/msht07_omont_gbba/
COMMENT: browsed videolectures.net yester and tried to watch cca 3 lectures on bioinformatics but the level of presentation was rather mediocre. topics interesting, but presented by some phd students in an uninteresting , hard-to-follow way.
but there is much more stuff, maybe i just didnt get representative sample, so hope to find something interesting.
OTHER SOURCE OF LECTURES/courses FROM MIT
opensource lectures from massachussets institute of technology.
pondelok 18. augusta 2008
Quantile regression
QUANTILE REGRESSION
BY ROGER KOENKER - GOOGLE BOOKS - ADVANCED MATHS
http://books.google.com/books?
id=Xi_dTAeAmGcC&pg=PA248&lpg=PA248&dq=quantile+regression+visualisation&source=web&ots=7JodXzWE8k&sig=0VWO5PTpFiAj7LaoARk3KkY8gok&hl=en&sa=X&oi=book_result&resnum=3&ct=result#PPA22,M1
BY ROGER KOENKER - GOOGLE BOOKS - ADVANCED MATHS
http://books.google.com/books?
id=Xi_dTAeAmGcC&pg=PA248&lpg=PA248&dq=quantile+regression+visualisation&source=web&ots=7JodXzWE8k&sig=0VWO5PTpFiAj7LaoARk3KkY8gok&hl=en&sa=X&oi=book_result&resnum=3&ct=result#PPA22,M1
REGRESSION ANOVA MODEL SELECTION
R_SQUARED preferably adjusted
F test
Mallow's C criterion
www-stat.stanford.edu/~jtaylo/courses/stats203/notes/selection.pdf by Jon Taylor
Larsen Stat course http://statmaster.sdu.dk/courses/st111/module08/index.html
Multiple regression -ppt. inc forward/backward/stepwise/best-subset regression, some maths
R_SQUARED preferably adjusted
F test
Mallow's C criterion
www-stat.stanford.edu/~jtaylo/courses/stats203/notes/selection.pdf by Jon Taylor
Larsen Stat course http://statmaster.sdu.dk/courses/st111/module08/index.html
Multiple regression -ppt. inc forward/backward/stepwise/best-subset regression, some maths
REGRESSION AND ANOVA TUTORIAL
NICE LIST OF LECTURES ON
REGRESSION AND ANOVA BY Dr Pia Veldt Larsen, Uni of Southern Denmark, Odense
- including regression model selection, residual analysis, factor analysis, logistic regression, and topics like transformation of variables etc.
REGRESSION AND ANOVA BY Dr Pia Veldt Larsen, Uni of Southern Denmark, Odense
- including regression model selection, residual analysis, factor analysis, logistic regression, and topics like transformation of variables etc.
streda 6. augusta 2008
statistics lectures, python, spss, R
a FANTASTIC COLLECTION of lectures on statistics - from basic concepts to advanced topics such as nonlinear regression. with examples.
- refers mainly to SPSS software, but this is marginal. MAINLY the mechanics behind the different tests is explained. VERY INSIGHTFUL.
dr FRIEL
******
seems like INTRO / TUTORIAL on the following topics.
ON PYTHON AND SPSS
on R - the open source statistical program "R"
- refers mainly to SPSS software, but this is marginal. MAINLY the mechanics behind the different tests is explained. VERY INSIGHTFUL.
dr FRIEL
******
seems like INTRO / TUTORIAL on the following topics.
ON PYTHON AND SPSS
on R - the open source statistical program "R"
utorok 29. apríla 2008
weighted least square regression
A technique for correcting the problem of heteroskedasticity by log-likelihood estimation of a weight that adjusts the errors of prediction
if some assumptions of ordinarly least square OLS regression do not hold.
.... in case of heteroscedasticity
.....unequal precision/reliability of datapoints
1. san Houston Uni - Weighted least squares regression XXX
http://www.shsu.edu/~icc_cmf/cj_789/weightedLeastSquares2.doc
- very good and detailed review of the technique, from the description of situations when to use WLS /ie if violation of homoscedasticity/ to detailed and very clear examples how to perform it /mainly applies to SPSS, the output is provided/.
- discusses both approaches on calculating weights 1/residualising the response variable 2/log-likelihood estimation of weights
- includes some basic mathematics, mostly well comprehensible college-level, formulas perfectly support the statements in text
/dr Charles M. Friel - author of this text provides lecture notes to a wide selection of statistical topics, comparable to Garson's Statnotes, in some topic I found dr Friel's explanations more poignant.
http://www.shsu.edu/~icc_cmf/directory.htm
2. statnotes - garson -including exemplification on SPSS ooutput - insightful, but not much regarding the mechanics of weight estimation / but maybe not so important/.
3. NIST Handbook - nice figures, comparison of WLS with alternative of nonlinear transformation of response and predictor variables.
if some assumptions of ordinarly least square OLS regression do not hold.
.... in case of heteroscedasticity
.....unequal precision/reliability of datapoints
1. san Houston Uni - Weighted least squares regression XXX
http://www.shsu.edu/~icc_cmf/cj_789/weightedLeastSquares2.doc
- very good and detailed review of the technique, from the description of situations when to use WLS /ie if violation of homoscedasticity/ to detailed and very clear examples how to perform it /mainly applies to SPSS, the output is provided/.
- discusses both approaches on calculating weights 1/residualising the response variable 2/log-likelihood estimation of weights
- includes some basic mathematics, mostly well comprehensible college-level, formulas perfectly support the statements in text
/dr Charles M. Friel - author of this text provides lecture notes to a wide selection of statistical topics, comparable to Garson's Statnotes, in some topic I found dr Friel's explanations more poignant.
http://www.shsu.edu/~icc_cmf/directory.htm
2. statnotes - garson -including exemplification on SPSS ooutput - insightful, but not much regarding the mechanics of weight estimation / but maybe not so important/.
3. NIST Handbook - nice figures, comparison of WLS with alternative of nonlinear transformation of response and predictor variables.
piatok 11. apríla 2008
relationship between
median, mean, mode
in skewed distributions
violations in discrete distributions and multimodal continuous ADVANCED, but accessible
by Hippel 2005 , journal of statistical education
transformations
Transformations
Statnotes - transformations - as part of testing assumptions, by Garson
- very nice, some pictures
Dallal's example of transformation in linear REGRESSION
RULE of THUMB: first transform the response variable y to correct heteroscedasticity (heterogeneity of variance) than apply transformation to predictiors to achieve linear relationship (bivariate scatterplot)
similar recommendations by NIST
Transformations:
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
NIST handbook of statistics
http://www.itl.nist.gov/div898/handbook/index.htm
from STATNOTES: To correct left (negative) skew, first subtract all values from the highest value plus 1, then apply square root, inverse, or logarithmic transforms.
Journal
chass
journal of statistical teaching and education ???
Statnotes - transformations - as part of testing assumptions, by Garson
- very nice, some pictures
Dallal's example of transformation in linear REGRESSION
RULE of THUMB: first transform the response variable y to correct heteroscedasticity (heterogeneity of variance) than apply transformation to predictiors to achieve linear relationship (bivariate scatterplot)
similar recommendations by NIST
Transformations:
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
NIST handbook of statistics
http://www.itl.nist.gov/div898/handbook/index.htm
from STATNOTES: To correct left (negative) skew, first subtract all values from the highest value plus 1, then apply square root, inverse, or logarithmic transforms.
Journal
chass
journal of statistical teaching and education ???
sobota 29. marca 2008
2 factor anova
from Dallals page Little Handbook of Statistical Practice
dairy farmer wished to determine which type of feed will produce the greatest yield of milk. From the research literature she is able to determine the mean milk output for each of the breeds she owns for each type of feed she is considering. As a practical matter, she can use only one type of feed for her herd.
Since she can use only one type of feed, she wants the one that will produce the greatest yield from her herd. She wants the feed type that produces the greatest yield when averaged over all breeds, even if it means using a feed that is not optimal for a particular breed. (In fact, it is easy to construct examples where the feed-type that is best on average is not the best for any breed!) The dairy farmer is interested in what the main effects have to say even in the presence of the interaction. She wants to compare
where the means are obtained by averaging over breed.
For the sake of rigor, it is worth remarking that this assumes the herd is composed of equal numbers of each breed. Otherwise, the feed-types would be compared through weighted averages with weights determined by the composition of the herd. For example, suppose feed A is splendid for Jerseys but mundane for Holsteins while feed B is splendid for Holsteins but mundane for Jerseys. Finally, let feed C be pretty good for both. In a mixed herd, feed C would be the feed of choice. If the composition of the herd were to become predominantly Jerseys, A might be the feed of choice with the gains in the Jerseys more than offsetting the losses in the Holsteins. A similar argument applies to feed B and a herd that is predominantly Holsteins.
dairy farmer wished to determine which type of feed will produce the greatest yield of milk. From the research literature she is able to determine the mean milk output for each of the breeds she owns for each type of feed she is considering. As a practical matter, she can use only one type of feed for her herd.
Since she can use only one type of feed, she wants the one that will produce the greatest yield from her herd. She wants the feed type that produces the greatest yield when averaged over all breeds, even if it means using a feed that is not optimal for a particular breed. (In fact, it is easy to construct examples where the feed-type that is best on average is not the best for any breed!) The dairy farmer is interested in what the main effects have to say even in the presence of the interaction. She wants to compare
where the means are obtained by averaging over breed.
For the sake of rigor, it is worth remarking that this assumes the herd is composed of equal numbers of each breed. Otherwise, the feed-types would be compared through weighted averages with weights determined by the composition of the herd. For example, suppose feed A is splendid for Jerseys but mundane for Holsteins while feed B is splendid for Holsteins but mundane for Jerseys. Finally, let feed C be pretty good for both. In a mixed herd, feed C would be the feed of choice. If the composition of the herd were to become predominantly Jerseys, A might be the feed of choice with the gains in the Jerseys more than offsetting the losses in the Holsteins. A similar argument applies to feed B and a herd that is predominantly Holsteins.
utorok 4. marca 2008
Linar mixed models - resources
Linar mixed models - resources
West, Galecki: Practical Approach
book-accompanying site with datasets, code, errata etc
http://www-personal.umich.edu/~bwest/almmussp.html
books google: Designing Experiments and Analyzing Data....
http://books.google.com/books?id=h-bMhmQMifsC&printsec=frontcover&dq=designing+experiments+and+analyzing+data&ei=pxfQR6mWHJPAzATw04iwBQ&sig=DlC1utBSuL1magJSjkdDxa-_-xw#PRA2-PA145,M1
- provides explanation of both ANOVA based mixed models with univariate and multivariate approach, as well as linear mixed models in the frame of multilevels modeling (chapters ,,,,)
- uses some mathematics, but in aN understandable form.
LIST of from site dedicated to HIERARCHICAL modeling
http://www.hlm-online.com/books/
multilevel data analysis - from basics - WEBCAST by Leroux
uwtv.org Multilevel data analysis
www.geocities.com/joophox/publist/whenwhy.pdf
Gelman
Eugen Demidenko LMM: Theory and Application
MULTILEVEL MODELING - SOFTWARE
http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/index.shtml
MM and R
http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/r.shtml
package lme (Pinheiro, Bates 2000)
more recent version - lmer, lme4 (2005)
www.r-project.org/doc/Rnews/Rnews_2005-1.pdf
for Splus, R by Fox (2002)
cran.r-project.org/doc/contrib/Fox-Companion/appendix-mixed-models.pdf
LINEAR MIXED MODELS
http://www2.chass.ncsu.edu/garson/pa765/multilevel.htm
no mathematical formulas
mainly refers to SPSS, but can can be useful as introduction for any platform
Hubbard Alan longitudinal data analysis
marginal models, generalized estimating equations GEE, with different link functions - Poisson regression etc.
provides lecture notes, and chapters from his textbook on the analysis of longitudinal data (quite readable, but at moments requires to think about vectors, matrix albebra etc., last chapter on Mixed models is not (yet?) available online), includes examples of code for STATA, SAS.
www.nyu.edu/its/socsci/Docs/SPSSMixed.ppt
comparison of mixed models with GLM - some formulas, many PRACTICAL points
www.spss.ch/upload/1107355943_LinearMixedEffectsModelling.pdf
www.spss.ch/upload/1126184451_Linear%20Mixed%20Effects%20Modeling%20in%20SPSS.pdf
gsic.syr.edu/manuals/spss/SPSS%20Advanced%20Models%2015.0.pdf
longitudinal data analysis - mixed models,
COURSES
ONLINE -
statistics.com - Galecki see above - also author of a textbook
www.statistics.com/ourcourses/mixedmodels/
also check - http://www.hlm-online.com/books/
http://www.csc.fi/english/csc/courses/archive/GLM2008
september 2008 - helsinki - Mixed models in R
MAXIMUM LIKELIHOOD ESTIMATION
explained - BGIM - Purcell
http://statgen.iop.kcl.ac.uk/bgim/mle/sslike_1.html
http://tigger.uic.edu/~hedeker/ml.html
SAS, SPSS
PPT
blog.case.edu/jjw17/2006/04/27/ZyzanskiSeminar4bPowerpoint.ppt
SURVIVAL mixed models for survival analysis
doi.wiley.com/10.1002/bimj.4710390102
jas.fass.org/cgi/reprint/77/E-Suppl_2/147.pdf
http://www.ingentaconnect.com/content/bpl/biom/2001/00000057/00000001/art00012
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4KFV26C-1&_user=949847&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000049130&_version=1&_urlVersion=0&_userid=949847&md5=8f89a4cc66b9fe62715703c0323305f0
http://www.wiwi.uni-bielefeld.de/~kauermann/survival/kauermann.pdf
http://links.jstor.org/sici?sici=0006-341X(200103)57%3A1%3C96%3AMMFSAW%3E2.0.CO%3B2-M
generalized linear model
online courses
XXXXXXX generalized - for quantitative, categorical, binary, count data XXXXXXXXXXXXX
http://genetics.agrsci.dk/statistics/courses/phd07/
in R
West, Galecki: Practical Approach
Linear Mixed Models: A Practical Guide Using Statistical Software
http://books.google.com/books?id=LSJ__7lDSdgC&printsec=frontcover&dq=west+galecki&ei=nPzOR7f0OJy8zATGpqmwBQ&sig=rI8DjvFAgy8W-5lcgbZX0WZTiXYbook-accompanying site with datasets, code, errata etc
http://www-personal.umich.edu/~bwest/almmussp.html
books google: Designing Experiments and Analyzing Data....
http://books.google.com/books?id=h-bMhmQMifsC&printsec=frontcover&dq=designing+experiments+and+analyzing+data&ei=pxfQR6mWHJPAzATw04iwBQ&sig=DlC1utBSuL1magJSjkdDxa-_-xw#PRA2-PA145,M1
- provides explanation of both ANOVA based mixed models with univariate and multivariate approach, as well as linear mixed models in the frame of multilevels modeling (chapters ,,,,)
- uses some mathematics, but in aN understandable form.
LIST of from site dedicated to HIERARCHICAL modeling
http://www.hlm-online.com/books/
multilevel data analysis - from basics - WEBCAST by Leroux
uwtv.org Multilevel data analysis
www.geocities.com/joophox/publist/whenwhy.pdf
Gelman
Data Analysis Using Regression and Multilevel/Hierarchical Models
Eugen Demidenko LMM: Theory and Application
MULTILEVEL MODELING - SOFTWARE
http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/index.shtml
MM and R
http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/r.shtml
package lme (Pinheiro, Bates 2000)
more recent version - lmer, lme4 (2005)
www.r-project.org/doc/Rnews/Rnews_2005-1.pdf
for Splus, R by Fox (2002)
cran.r-project.org/doc/contrib/
LINEAR MIXED MODELS
http://www2.chass.ncsu.edu/garson/pa765/multilevel.htm
no mathematical formulas
mainly refers to SPSS, but can can be useful as introduction for any platform
Hubbard Alan longitudinal data analysis
marginal models, generalized estimating equations GEE, with different link functions - Poisson regression etc.
provides lecture notes, and chapters from his textbook on the analysis of longitudinal data (quite readable, but at moments requires to think about vectors, matrix albebra etc., last chapter on Mixed models is not (yet?) available online), includes examples of code for STATA, SAS.
www.nyu.edu/its/socsci/Docs/SPSSMixed.ppt
comparison of mixed models with GLM - some formulas, many PRACTICAL points
www.spss.ch/upload/1107355943_LinearMixedEffectsModelling.pdf
www.spss.ch/upload/1126184451_Linear%20Mixed%20Effects%20Modeling%20in%20SPSS.pdf
gsic.syr.edu/manuals/spss/SPSS%20Advanced%20Models%2015.0.pdf
longitudinal data analysis - mixed models,
COURSES
ONLINE -
statistics.com - Galecki see above - also author of a textbook
www.statistics.com/ourcourses/mixedmodels/
also check - http://www.hlm-online.com/books/
http://www.csc.fi/english/csc/courses/archive/GLM2008
september 2008 - helsinki - Mixed models in R
MAXIMUM LIKELIHOOD ESTIMATION
explained - BGIM - Purcell
http://statgen.iop.kcl.ac.uk/bgim/mle/sslike_1.html
http://tigger.uic.edu/~hedeker/ml.html
SAS, SPSS
PPT
blog.case.edu/jjw17/2006/
SURVIVAL mixed models for survival analysis
jas.fass.org/cgi/reprint/77/E-Suppl_2/147.pdf
http://www.ingentaconnect.com/content/bpl/biom/2001/00000057/00000001/art00012
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4KFV26C-1&_user=949847&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000049130&_version=1&_urlVersion=0&_userid=949847&md5=8f89a4cc66b9fe62715703c0323305f0
http://www.wiwi.uni-bielefeld.de/~kauermann/survival/kauermann.pdf
http://links.jstor.org/sici?sici=0006-341X(200103)57%3A1%3C96%3AMMFSAW%3E2.0.CO%3B2-M
generalized linear model
online courses
XXXXXXX generalized - for quantitative, categorical, binary, count data XXXXXXXXXXXXX
http://genetics.agrsci.dk/statistics/courses/phd07/
in R
pondelok 4. februára 2008
EXCEL MACRO resources
links to some fora dealing with macros/VBA script for different tasks
eg hiding row/column depending on value in a cell
solution from allexperts.com
thread from ozgrid.com
eg hiding row/column depending on value in a cell
solution from allexperts.com
thread from ozgrid.com
nedeľa 3. februára 2008
piatok 1. februára 2008
SPSS automation OMS
from SPSS ARCHIVE
Correlation output using OMS
OMS COMMAND OUPUT XML SYNTAX
UCLA SPSS OMS TO SPSS FILE
UNI MANNHEIM STH WITH DDI ??? XML CONVERTER
http://db.zuma-mannheim.de/DDI/Workshop/2007-10-24/DDI%203%20Workshop/SPSS%20DDI%20Converter/Test/sample_setups.txt
http://bib.kuleuven.be/ebib/data/handleidingen/spss_programming_and_data_management.pdf
OMS p309 data management levesQUE
SPSS XML DDI DDI DATA DOCUMENTATION INITIATIVE
http://xml.coverpages.org/xslSoftware.html 2004 CF COCOON,
SPSS tutorials GERMAN
NICE TUTORIALS IN FORM OF FLASH
BY HANS GRUENER, FREIE UNI BERLIN
RECENT
ON STATISTIC PROCEDURES, INTRO IN SYNTAX, SCRIPT, MACRO.
SPSS v12.
NICE, cave ö german
BY HANS GRUENER, FREIE UNI BERLIN
RECENT
ON STATISTIC PROCEDURES, INTRO IN SYNTAX, SCRIPT, MACRO.
SPSS v12.
NICE, cave ö german
piatok 25. januára 2008
SPSS for dummies
http://media.wiley.com/product_data/excerpt/48/04701134/0470113448.pdf
SPSS for dummies - 1st chapter- sample
by griffith
includes chapters on command syntax, Python , and VBS scripting.
SPSS for dummies - 1st chapter- sample
by griffith
includes chapters on command syntax, Python , and VBS scripting.
štvrtok 24. januára 2008
python textbook
learning to progam PYTHON ale aj o VBScript a JavaScript by alan gauld
česky preklad !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
looks interesting, readable.
update How to Think Like a (Python) Programmer 2007
http://www.greenteapress.com/thinkpython/thinkPP.pdf
the update of the following book. ... by downey
How to Think Like a Computer Scientist 2002
Learning with Python
Allen Downey
Jerey Elkner
Chris Meyers
baldwin HTML - Python
česky preklad !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
looks interesting, readable.
update How to Think Like a (Python) Programmer 2007
http://www.greenteapress.com/thinkpython/thinkPP.pdf
the update of the following book. ... by downey
How to Think Like a Computer Scientist 2002
Learning with Python
Allen Downey
Jerey Elkner
Chris Meyers
baldwin HTML - Python
Prihlásiť na odber:
Komentáre (Atom)