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st: 3rd German Stata Users' Group Meeting: Announcement and Program


From   Ulrich Kohler <kohler@wz-berlin.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: 3rd German Stata Users' Group Meeting: Announcement and Program
Date   Tue, 8 Mar 2005 11:30:36 +0100

3rd German Stata Users' Group Meeting: Announcement and Program
===============================================================

The 3rd German Stata Users' Group Meeting will be held at the 
Wissenschaftszentrum Berlin (http://www.wz-berlin.de) on Friday, 8th April 
2005.

The content of the meeting has been organised by Johannes Giesecke, Humboldt 
University Berlin (johannes.giesecke@rz.hu-berlin.de ) and Ulrich Kohler, WZB 
(kohler@wz-berlin.de) and Willi Sauerbrei (wfs@imbi.uni-freiburg.de). The 
logistics are being organised by Dittrich and Partner (http://www.dpc.de), 
the distributor of Stata in several countries including Germany and Austria.

The meeting is open to all interested, and we are happy if Stata users from
neighbouring countries would join us. StataCorp will be represented. The
conference language will be English due to the 'international' nature of the
meeting and the participation of non-German guest speakers. There will be a
"wishes and grumbles" session at which you may air your thoughts to Stata
developers. There will also be an optional informal meal at a Berlin 
restaurant on Friday evening (at additional cost of 20 Euro).

Participants are asked to travel on their own fees. There will be a small
conference fee (regular 20 Euro, students 10 Euro) to cover costs for coffee,
teas, and luncheons.

For further information on registration, please contact anke.mrosek@dpc.de. 
Mrs. Mrosek will also assist you in finding an accommodation. For general 
information about the meeting see also http://www.stata.com/berlin05.


Schedule of the 3rd German Stata Users' Group Meeting
-----------------------------------------------------

 8:45 Registration and coffee/tea

 9:15 Welcome
      Ulrich Kohler?, DPC

 9:30 Multivariable regression models with continuous covariates, with 
      a practical emphasis on fractional polynomials and applications in
      clinical epidemiology
      Patrick Royston, Cancer Division, MRC Clinical Trials Unit

      Regression models play a central role in epidemiology and clinical
      studies. In epidemiology the emphasis is typically either on determining
      whether a given risk factor affects the outcome of interest (adjusted
      for confounders), or on estimating a dose/response curve for a given
      factor, again adjusting for confounders. An important class of clinical
      studies is the so-called prognostic factors studies, in which the
      outcome for patients with chronic diseases such as cancer is predicted
      from various clinical features. In both application areas, it is almost
      always necessary to build a multivariable model incorporating known or
      suspected influential variables while eliminating those found to be
      unimportant.

      It is commonplace for risk or prognostic factors to be measured
      on a continuous scale, an obvious example being a person's age.
      Conventionally, such factors are either modelled as linear functions
      or are converted into categories according to some chosen set
      of cut-points. However, categorisation and use of the resulting
      estimates is a procedure known to be fraught with difficulty. A linear 
      function may fit the data badly and give misleading estimates of risk.       
      Therefore, reliable approaches for representing the effects of 
      continuous factors in multivariable models are urgently needed.

      Building multivariable regression models by selecting influential
      covariates and determining the functional form of the relationship
      between a continuous covariate and the outcome when analysing data
      from clinical and epidemiological studies is the main concern
      of this talk. Systematic procedures which combine selection of
      influential variables with determination of functional form for
      continuous factors are rare. Analysts may apply their individual
      subjective preferences for each part of the  model-building process,
      estimate parameters for several models and then decide on the
      final strategy according to the results they find. By contrast,
      we will present here the multivariable fractional polynomial (MFP) 
      approach as a systematic way to determine a multivariable regression 
      model. The MFP approach was made generally available to Stata users
      in version 8 as the -mfp- command. Major concerns will be discussed,
      including robustness and possible model instability. Regarding
      determination of the functional form, we will also discuss some
      alternatives with more emphasis on local estimation of the function
      (e.g. splines). The MFP procedure may be used for various types
      of regression models (linear regression model, logistic model,
      Cox model, and many more). Examples with real data will be used as
      illustrations.

10:30 Coffee

10:40 Response Surface Modelling Using Stata
      Jeroen Weesie, University of Utrecht

11:20 Standard Errors for the Blinder-Oaxaca Decomposition
      Ben Jann, ETH Zürich

      The decomposition technique introduced by Blinder (1973) and Oaxaca
      (1973) is widely used to study outcome differences between groups. For
      example, the technique is commonly applied to the analysis of the gender
      wage gap. However, despite the procedure's frequent use, very little
      attention has been paid to the issue of estimating the sampling
      variances of the decomposition components. We therefore suggest an
      approach that introduces consistent variance estimators for several
      variants of the decomposition. The accuracy of the new estimators under
      ideal conditions is illustrated with the results of a Monte Carlo
      simulation. As a second check, the estimators are compared to bootstrap
      results obtained using real data. In contrast to previously proposed
      statistics, the new method takes into account the extra variation
      imposed by stochastic regressors.

12:00 Lunch

13:00 Estimating IRT models with gllamm
      Herbert Matschinger, Department of Psychiatry, University of Leipzig

      At least in psychology much attention is paid to different forms of 
      IRT models and particularly the Rasch model, since it is the only model
      featuring specific objectivity which enables what is called a "fair
      comparison" with respect to the latent dimension to be measured. Rasch
      models have been developed both for binary and ordered multicategory
      items as well as for models with difficulty parameter only (one
      parameter model) and models with difficulty and discrimination
      parameters (two parameter model). This presentation will focus on the
      possibilities and restrictions in estimating these models with gllamm.
      As an example we adopt data for the Psychological General Well-Being
      Scale (WHO-5) which was employed in a study of the WHO to develop an
      instrument to asses the quality of life of the elderly (65+). It 
      consists of 5 items and 5 ordinal categories each. Data come from 5
      different European countries. 

      The effect of collapsing categories as well as item differential
      functioning with respect to the countries will be evaluated. The
      possibility of modelling the heterogeneity of the item-categories will
      be discussed. The location of the countries on the random factor will
      be estimated simultaneously. 

13:40 A Survey on Survey Statistics: What is done, can be done in Stata, 
      and what's missing 
      Frauke Kreuter, Richard Valliant (Joint Program in Survey Methodology
      University of Maryland, College Park)

      Among survey statisticians Stata is increasingly recognized as one of
      the more powerful statistical software packages for the analysis of
      complex survey data. This paper will survey the capabilities of Stata to
      analyze complex survey data. We will briefly review and compare
      different methods for variance estimation for stratified and clustered
      samples, and discuss the handling of survey weights. Examples will be
      given for the practical importance of Stata's survey capabilities. In
      addition we will point to statistical solutions that aren't yet part of
      the official package, and review user written ados that currently extend
      Stata's survey capabilities. Among the specific topics we will cover are
      replication variance estimation (jackknife, balanced repeated
      replication, and the bootstrap), issues associated with degrees of
      freedom and domain estimates, quantile estimation, and some concerns
      related to model fitting using survey data.

14:20 Coffee

14:35 Who do you trust while bubbles grow and blow? A comparative analysis of
      the explanatory power of accounting and patent information for the
      market values of German firms 
      Fred Ramb, Deutsche Bundesbank
      Markus Reitzig, The Copenhagen Business School

      We present a theoretical and empirical analysis of the fitness of
      national German (German Commercial Code ­ Handelsgesetzbuch (HGB)) and
      international (IAS and US-GAAP) accounting information, as well as
      European patent data to explain the market values of German
      manufacturing firms. For the chosen volatile period from 1997 to 2002,
      cautious national accounting information does not correlate with the 
      firms' residual market values (RMV). International accounting
      information makes no meaningful contribution to explaining firms' RMV
      and seems to measure over-investment only. Finally, patents counted at
      the individual country level correlate with the firms' RMV. To the best
      of our knowledge this is the first paper which use a panel fixed effects
      estimator for a non-linear equation. We estimate the model using an 
      algorithm programmed with Stata and Ox.  

15:15 Simple Thematic Mapping in Stata
      Mauritio Pisati, University of Milan

      Thematic maps illustrate the spatial distribution of one or more 
      variables of interest within a given geographical unit. The purpose of
      this talk is to present version 2.0 of the -tmap- package, a suite of
      Stata programs designed to draw several kinds of thematic map. The first
      public release of -tmap- was published in The Stata Journal in 2004.
      This presentation will focus on the new features of the package.

15:55 Coffee

16:10 Stata implementation at Berlecon Research: Experiences made - 
      requirements for a Professional Services Company
      Andreas Stiehler, Berlecon

      Berlecon Research is a German-based research company that analyzes the 
      potential of new technologies within the IT, Internet and mobile 
      industry in Germany and Europe. The analysis of survey data - typically 
      deliverd by market research companies - are an integral part of the 
      Berlecon activities. In 2004, the company implemented Stata 8 in order 
      to streamline the data processing and to design high quality graphs and 
      tables. The presentation will discuss the specific requirements for 
      Professional Research organisations needed by Stata program. Thereby, 
      main challenges and ways chosen to overcome them - as far as the Stata 
      usage by Berlecon - will be explained. Lastly, a wish list for the 
      Stata corporation will be presented.

16:50 Recent developments in Stata
      David Drukker, StataCorp

17:30 Coffee

17:45 Report to the Users
      Bill Gould, Stata Corp

18:30 Wishes and Grumbles

19:15 End of the Meeting





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