Re: [ABE-L]: The International Journal of Biostatistics - new journal (fwd)

[assuncao@est.ufmg.br]

Pessoal,

Esta revista que a Clarice chamou a atencao em e-mail anterior tem um
sistema de revisao de artigos muito interessante. Os pareceristas 
tem 21 dias para fazer uma revisao. Para assegurar que a revisao 
seja realmente feita e seja de qualidade, a revista 
tem um sistema "bancario" onde autores de artigos ja aceitos 
sao obrigados a fazerem revisoes sob pena de terem $$$ descontado 
do cartao de credito. A moeda e' revisao por $$$.

Muito interessante as regras. Leiam se quiserem distrair uns minutos 
daquele trabalho arduo de revisao de artigos :-)

Renato  

Citando "Clarice G.B. Demetrio" <clarice@carpa.ciagri.usp.br>:

> ---------- Forwarded message ----------
> Date: Tue, 10 Jan 2006 15:49:46 -0800 (PST)
> From: Nicholas P. Jewell <mm-9510-505761@bepress.com>
> To: clarice@carpa.ciagri.usp.br
> Subject: The International Journal of Biostatistics - new journal
> 
> 
> 
> The Berkeley Electronic Press - together with editors Nicholas P. Jewell,
> David Freedman, and Mark van der Laan of University of California,
> Berkeley; Raymond Carroll of Texas A&M University; and James Robins of
> Harvard University - is pleased to announce the launch of the International
> Journal of Biostatistics (IJB). IJB is a peer-reviewed e-journal publishing
> new biostatistical models and methods, new statistical theory, as well as
> original applications of statistical methods, for important practical
> problems arising from the biological, medical, public health, and
> agricultural sciences. To view any of the recently published articles,
> simply click on the links below. Full citations and abstracts, as well as
> additional IJB details, follow at bottom of message.
> 
> 
> 
> Xiang Guo and Anastasios Tsiatis "A Weighted Risk Set Estimator for Survival
> Distributions in Two-Stage Randomization Designs with Censored Survival
> Data".
> http://www.bepress.com/ijb/vol1/iss1/1
> 
> Nicholas P. Jewell and Biao Wm. Lu "Some Variants of the Backcalculation
> Method for Estimation of Disease Incidence: An Application to Multiple
> Sclerosis Data from the Faroe Islands".
> http://www.bepress.com/ijb/vol1/iss1/2
> 
> Moulinath Banerjee and Jon A. Wellner "Score Statistics for Current Status
> Data: Comparisons with Likelihood Ratio and Wald Statistics".
> http://www.bepress.com/ijb/vol1/iss1/3
> 
> Mark J. van der Laan, Maya L. Petersen, and Marshall M. Joffe
> "History-Adjusted Marginal Structural Models and Statically-Optimal
> Dynamic Treatment Regimens".
> http://www.bepress.com/ijb/vol1/iss1/4
> 
> Ian W. McKeague and Yichuan Zhao "Comparing Distribution Functions Via
> Empirical Likelihood".
> http://www.bepress.com/ijb/vol1/iss1/5
> 
> 
> 
> __________________________
> ABOUT INTERNATIONAL JOURNAL OF BIOSTATISTICS
> 
> The International Journal of Biostatistics (IJB) covers the entire range of
> biostatistics, from theoretical advances to relevant and sensible
> translations of a practical problem into a statistical framework, including
> advances in biostatistical computing. Electronic publication also allows for
> data and software code to be appended, and opens the door for reproducible
> research allowing readers to easily replicate analyses described in a paper.
> Both original research and review articles will be warmly received, as will
> articles applying sound statistical methods to practical problems. For more
> details, or to submit your next paper, visit:
> 
> http://www.bepress.com/ijb
> 
> 
> EDITORIAL BOARD
> 
> Ron Brookmeyer		Johns Hopkins University
> Daniel Commenges	Inserm, Bordeaux
> Christl Donnelly	Imperial College, London
> Jack Kalbfleisch	University of Michigan
> Charles Kooperberg	Fred Hutchinson Cancer Research Center
> Michael R. Kosorok	University of Wisconsin, Madison
> Ian McKeague		Columbia University
> Stephan Morgenthaler	L'Ecole Polytechnique Fédérale de Lausanne
> Patricia Solomon	University of Adelaide
> 
> __________________________
> ABSTRACTS & CITATIONS OF NEWLY PUBLISHED ARTICLES
> 
> 
> Xiang Guo and Anastasios Tsiatis (2005) "A Weighted Risk Set Estimator for
> Survival Distributions in Two-Stage Randomization Designs with Censored
> Survival Data", The International Journal of Biostatistics: Vol. 1: No. 1,
> Article 1.
> http://www.bepress.com/ijb/vol1/iss1/1
> 
> ABSTRACT:
> In many clinical trials related to diseases such as cancers and HIV, patients
> are treated by different combinations of therapies. This leads to two-stage
> designs, where patients are initially randomized to a primary therapy and
> then depending on disease remission and patients' consent, a maintenance
> therapy will be randomly assigned. In such designs, the effects of different
> treatment policies, i.e., combinations of primary and maintenance therapy are
> of great interest. In this paper, we propose an estimator for the survival
> distribution for each treatment policy in such two-stage studies with
> right-censoring using the method of weighted estimation equations within risk
> sets. We also derive the large-sample properties. The method is demonstrated
> and compared with other estimators through simulations and applied to analyze
> a two-stage randomized study with leukemia patients.
> 
> 
> Nicholas P. Jewell and Biao Wm. Lu (2005) "Some Variants of the
> Backcalculation Method for Estimation of Disease Incidence: An Application to
> Multiple Sclerosis Data from the Faroe Islands", The International Journal of
> Biostatistics: Vol. 1: No. 1, Article 2.
> http://www.bepress.com/ijb/vol1/iss1/2
> 
> ABSTRACT:
> Backcalculation is a technique that was originally developed for the study of
> HIV incidence. Here we introduce some variants of the estimation technique
> that allow for (i) correlation of the unobserved disease incidence counts,
> and (ii) the use of a smoothing step as part of the maximizing step in the EM
> algorithm to reduce instability due to small diagnosis counts. Both of these
> issues can be important in the analysis of small "epidemics". In addition,
> identification of correlation between diagnosis counts provides indirect
> evidence of correlation among unobserved incidence counts, hinting at the
> possibility of an infectious agent. We illustrate the ideas by reconstructing
> an incidence intensity function for the onset of multiple sclerosis, using
> data from the Faroe Islands. Previously, this data had been examined
> statistically, by Joseph, Wolfson & Wolfson (1990), to address the issue of
> infectiousness of multiple sclerosis. We argue that the incidence function
> cannot directly shed light on the enigmatic origin of multiple sclerosis in
> the Faroe Islands during World War II, and, in particular, cannot
> discriminate between hypotheses of an infectious or environmental agent.
> 
> 
> Moulinath Banerjee and Jon A. Wellner (2005) "Score Statistics for Current
> Status Data: Comparisons with Likelihood Ratio and Wald Statistics", The
> International Journal of Biostatistics: Vol. 1: No. 1, Article 3.
> http://www.bepress.com/ijb/vol1/iss1/3
> 
> ABSTRACT:
> In this paper we introduce three natural "score statistics" for testing the
> hypothesis that F(t_0)takes on a fixed value in the context of nonparametric
> inference with current status data. These three new test statistics have
> natural interpretations in terms of certain (weighted) L_2 distances, and are
> also connected to natural "one-sided" scores. We compare these new test
> statistics with the analogue of the classical Wald statistic and the
> likelihood ratio statistic introduced in Banerjee and Wellner (2001) for the
> same testing problem. Under classical "regular" statistical problems the
> likelihood ratio, score, and Wald statistics all have the same chi-squared
> limiting distribution under the null hypothesis. In sharp contrast, in this
> non-regular problem all three statistics have different limiting
> distributions under the null hypothesis. Thus we begin by establishing the
> limit distribution theory of the statistics under the null hypothesis, and
> discuss calculation of the relevant critical points for the test statistics.
> Once the null distribution theory is known, the immediate question becomes
> that of power. We establish the limiting behavior of the three types of
> statistics under local alternatives. We have also compared the power of these
> five different statistics via a limited Monte-Carlo study. Our conclusions
> are: (a) the Wald statistic is less powerful than the likelihood ratio and
> score statistics; and (b) one of the score statistics may have more power
> than the likelihood ratio statistic for some alternatives.
> 
> 
> Mark J. van der Laan, Maya L. Petersen, and Marshall M. Joffe (2005)
> "History-Adjusted Marginal Structural Models and Statically-Optimal Dynamic
> Treatment Regimens", The International Journal of Biostatistics: Vol. 1: No.
> 1, Article 4.
> http://www.bepress.com/ijb/vol1/iss1/4
> 
> ABSTRACT:
> Marginal structural models (MSM) provide a powerful tool for estimating the
> causal effect of a treatment. These models, introduced by Robins, model the
> marginal distributions of treatment-specific counterfactual outcomes,
> possibly conditional on a subset of the baseline covariates. Marginal
> structural models are particularly useful in the context of longitudinal data
> structures, in which each subject's treatment and covariate history are
> measured over time, and an outcome is recorded at a final time point.
> However, the utility of these models for some applications has been limited
> by their inability to incorporate modification of the causal effect of
> treatment by time-varying covariates. Particularly in the context of clinical
> decision making, such time-varying effect modifiers are often of considerable
> or even primary interest, as they are used in practice to guide treatment
> decisions for an individual. In this article we propose a generalization of
> marginal structural models, which we call history-adjusted marginal
> structural models (HA-MSM). These models allow estimation of adjusted causal
> effects of treatment, given the observed past, and are therefore more
> suitable for making treatment decisions at the individual level and for
> identification of time-dependent effect modifiers. Specifically, a HA-MSM
> models the conditional distribution of treatment-specific counterfactual
> outcomes, conditional on the whole or a subset of the observed past up till a
> time-point, simultaneously for all time-points. Double robust inverse
> probability of treatment weighted estimators have been developed and studied
> in detail for standard MSM. We extend these results by proposing a class of
> double robust inverse probability of treatment weighted estimators for the
> unknown parameters of the HA-MSM. In addition, we show that HA-MSM provide a
> natural approach to identifying the dynamic treatment regimen which follows,
> at each time-point, the history-adjusted (up till the most recent time point)
> optimal static treatment regimen. We illustrate our results using an example
> drawn from the treatment of HIV infection.
> 
> 
> Ian W. McKeague and Yichuan Zhao (2005) "Comparing Distribution Functions Via
> Empirical Likelihood", The International Journal of Biostatistics: Vol. 1:
> No. 1, Article 5.
> http://www.bepress.com/ijb/vol1/iss1/5
> 
> ABSTRACT:
> This paper develops empirical likelihood based simultaneous confidence bands
> for differences and ratios of two distribution functions from independent
> samples of right-censored survival data. The proposed confidence bands
> provide a flexible way of comparing treatments in biomedical settings, and
> bring empirical likelihood methods to bear on important target functions for
> which only Wald-type confidence bands have been available in the literature.
> The approach is illustrated with a real data example.
> 
> 
> 
> 
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