Literature DB >> 20563220

Principal Point Classification: Applications to Differentiating Drug and Placebo Responses in Longitudinal Studies.

Thaddeus Tarpey1, Eva Petkova.   

Abstract

Principal points are cluster means for theoretical distributions. A discriminant methodology based on principal points is introduced. The principal point classification method is useful in clinical trials where the goal is to distinguish and differentiate between different treatment effects. Particularly, in psychiatric studies where placebo response rates can be very high, the principal point classification is illustrated to distinguish specific drug responders from non-specific placebo responders.

Entities:  

Year:  2010        PMID: 20563220      PMCID: PMC2885612          DOI: 10.1016/j.jspi.2009.07.030

Source DB:  PubMed          Journal:  J Stat Plan Inference        ISSN: 0378-3758            Impact factor:   1.111


  7 in total

1.  Finite mixture modeling with mixture outcomes using the EM algorithm.

Authors:  B Muthén; K Shedden
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

2.  A typological model for estimation of drug and placebo effects in depression.

Authors:  Donald C Ross; Frederick M Quitkin; Donald F Klein
Journal:  J Clin Psychopharmacol       Date:  2002-08       Impact factor: 3.153

3.  Using a Bayesian latent growth curve model to identify trajectories of positive affect and negative events following myocardial infarction.

Authors:  Michael R Elliott; Joseph J Gallo; Thomas R Ten Have; Hillary R Bogner; Ira R Katz
Journal:  Biostatistics       Date:  2005-01       Impact factor: 5.899

4.  Optimal Partitioning for Linear Mixed Effects Models: Applications to Identifying Placebo Responders.

Authors:  Thaddeus Tarpey; Eva Petkova; Yimeng Lu; Usha Govindarajulu
Journal:  J Am Stat Assoc       Date:  2010-01-01       Impact factor: 5.033

5.  Linear Transformations and the k-Means Clustering Algorithm: Applications to Clustering Curves.

Authors:  Thaddeus Tarpey
Journal:  Am Stat       Date:  2007-02       Impact factor: 8.710

6.  A Parametric k-Means Algorithm.

Authors:  Thaddeus Tarpey
Journal:  Comput Stat       Date:  2007-04       Impact factor: 1.000

7.  Use of pattern analysis to identify true drug response. A replication.

Authors:  F M Quitkin; J D Rabkin; J M Markowitz; J W Stewart; P J McGrath; W Harrison
Journal:  Arch Gen Psychiatry       Date:  1987-03
  7 in total
  2 in total

1.  Principal points analysis via p-median problem for binary data.

Authors:  Haruka Yamashita; Yoshinobu Kawahara
Journal:  J Appl Stat       Date:  2019-10-09       Impact factor: 1.416

2.  Stratified Psychiatry via Convexity-Based Clustering with Applications Towards Moderator Analysis.

Authors:  Thaddeus Tarpey; Eva Petkova; Liangyu Zhu
Journal:  Stat Interface       Date:  2016-07-01       Impact factor: 0.582

  2 in total

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