Computing Distributions for Exact Logistic Regression

Hirji, Karim F.; Mehta, Cyrus R.; Patel, Nitin R.

doi:10.2307/2289388

Cited by 112 publications

(69 citation statements)

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“…We calculated exact odds ratios for significant values in the univariate and multivariate models. 15 The predictor variables of interest included all data recorded at study entry. A P value of Ͻ .05 was considered significant.…”

Section: Study End Points and Statistical Analysismentioning

confidence: 99%

“Hospital at Home” for Neuromuscular Disease Patients With Respiratory Tract Infection: A Pilot Study

Vianello¹,

Savoia²,

Pipitone

et al. 2013

Respir Care

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BACKGROUND:The "hospital-at-home" model may provide adequate care without an adverse effect on clinical outcome, and is generally well received by users. Our objective was to compare hospital-at-home and in-patient hospital care for neuromuscular disease (NMD) patients with respiratory tract infections. METHODS: We conducted a prospective randomized controlled trial in a university teaching hospital offering secondary care service to a population of approximately 500,000. We recruited selected NMD patients with respiratory tract infection for whom hospital admission had been recommended after medical assessment. Hospital-at-home was provided as an alternative to in-patient admission. The main outcome measures were need for hospitalization, treatment failure, time to recovery, death during the first 3 months following exacerbation, and cost of patient care. RESULTS: Among 59 consecutive NMD patients eligible for the study, 53 met the criteria for hospital-at-home. Twenty-six subjects were randomized to home care and 27 to hospital care. No significant differences were found in treatment failure (8/26 vs 13/27, P ‫؍‬ .19), time to recovery (8.9 ؎ 4.6 vs 9 ؎ 8.9 d, P ‫؍‬ .21), or mortality at 3 months (3/26 vs 4/27 deaths, P ‫؍‬ .42) between the groups. Hospital-at-home failure was independently correlated with type of NMD (P ‫؍‬ .004) with an odds ratio of failure of 17.3 (95% CI 2.1 to infinity) for subjects with amyotrophic lateral sclerosis. The total and daily direct cost of patient healthcare was significantly lower for the subjects who were successfully treated at home, compared to the hospitalized individuals. CONCLUSIONS: Hospital-at-home is an effective alternative to hospital admission for selected NMD patients with respiratory tract infections.

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Section: Study End Points and Statistical Analysismentioning

confidence: 99%

“Hospital at Home” for Neuromuscular Disease Patients With Respiratory Tract Infection: A Pilot Study

Vianello¹,

Savoia²,

Pipitone

et al. 2013

Respir Care

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“…Exact logistic regression was used with sparse data. 19 Due to incompleteness of data, separate analyses were performed for patients with cytogenetic data. Multivariate analyses for CR and OS included patients with complete covariate data.…”

Section: Statistical Considerationsmentioning

confidence: 99%

Prognostic variables in newly diagnosed children and adolescents with acute myeloid leukemia: Children's Cancer Group Study 213

et al. 2002

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The objective of this study was to identify biologic parameters that were associated with either exceptionally good or poor outcome in childhood acute myeloid leukemia (AML). Among the children with AML who entered Children's Cancer Group trial 213, 498 patients without Down syndrome or acute promyelocytic leukemia (APL) comprise the basis for this report. Univariate comparisons of the proportion of patients attaining complete remission after induction (CR) indicate that, at diagnosis, male gender, low platelet count (р20 000/ l), hepatomegaly, myelodysplastic syndrome (MDS), French-AmericanBritish (FAB) category M5, high (Ͼ15%) bone marrow (BM) blasts on day 14 of the first course of induction, and +8 are associated with lower CR rates, while abnormal 16 is associated with a higher CR rate. Multivariate analysis suggests high platelet count at diagnosis (Ͼ20 000/ l), absence of hepatomegaly, р15% day 14 BM blast percentage, and abnormal 16 are independent prognostic factors associated with better CR. Univariate analysis demonstrated a significant favorable relationship between platelet count at diagnosis (Ͼ20 000/ l), absence of hepatomegaly, low percentage of BM blasts (р15%), and abnormal 16 with overall survival. Absence of hepatomegaly, р15% day 14 BM blast percentage, and abnormal 16 were determined to be independent prognostic factors associated with better survival. Leukemia (2002) 16, 601-607.

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“…For larger problems, the MC hypothesis test approximates that distribution by sampling. Algorithms have been developed to extend the exact test to some logistic regressions, for example, (Hirji et al, 1987;Mehta & Patel, 1995), and yet for larger problems, an approximation by simulation is necessary (Zamar et al, 2007). The MC hypothesis test is not discussed in most statistics texts, perhaps a signal that it is not considered necessary for most common statistical problems.…”

Section: Understanding Sampling Distributionsmentioning

confidence: 99%

“…For larger problems, the MC hypothesis test approximates that distribution by sampling. Algorithms have been developed to extend the exact test to some logistic regressions, for example, (Hirji et al, 1987;Mehta & Patel, 1995), and yet for larger problems, an approximation by simulation is necessary (Zamar et al, 2007 Besag & Diggle, 1977;Ripley, 1977;Marriott, 1979). Random processes are hypothesized to cause things (animals, plants, etc.)…”

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confidence: 99%

Monte Carlo Analysis in Academic Research

Johnson

2013

Oxford Handbooks Online

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Monte Carlo analysis is a research strategy that incorporates randomness into the design, implementation or evaluation of theoretical models. It began in the 1940s, when the development of computer hardware and mathematical models made it possible to generate streams of random numbers. These random number streams are combined with mathematical models in order to create models and evaluate theories of random processes. This chapter attempts to tame this diverse, unmanageable collection of concepts and methods by dividing simulation projects into three types. The first, commonly called "Monte Carlo simulation," is used to evaluate statistical estimators. When an estimation procedure is proposed, it is standard procedure to test it against a variety of simulated research problems. A second type of project, referred to as "Markov chain Monte Carlo" (or MCMC), helps researchers to draw conclusions about complicated probability models for which conventional research strategies do not yield insights. The third 1 type of project arises in the study of complex systems, which are characterized by a large number of loosely interconnected, autonomous elements. Commonly known as agent-based models, these simulations have found enthusiastic advocates in environmental and social sciences.Keywords: Monte Carlo, Markov chain Monte Carlo (MCMC), pseudo random number generation (PRNG), Bayesian statistics, agent-based modeling Monte Carlo (MC) analysis is a general term that refers to research that employs random numbers, usually in the form of a computer model (or simulation). Although this research began in the natural sciences, computer science, and mathematics, it is now widely applied in social science as well. This essay attempts to explain the fundamental ideas that spurred the creation of these new procedures as well as their eventual adaptation for use in social science research.This chapter is not a "how to" guide for simulation, but rather it is a "what for" or "why you might want to" guide. Some of the difficulties that arise in MC research projects are considered as well. It begins with some background information on the development of computers and algorithms for random numbers. After that, the chapter takes up applications in the evaluation of proposed statistical estimators, the practice of Bayesian statistics via computer simulation, and investigation of complex systems through agent-based models. Some conclusions about the challenges that face the field are presented, along with a conclusion. A significant part of the presentation is about the exciting developments that have occurred since 1990. Rapid improvements in hardware and software have opened up opportunities for scholars to work with models that were previously prohibited by conceptual and technical barriers. At the current time, we are able to conceptualize and implement models that were simply impossible just 10 years ago. The extremely rapid progress has been driven by a fruitful interaction of substantive researchers in the natural and social science...

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Computing Distributions for Exact Logistic Regression

Cited by 112 publications

References 0 publications

“Hospital at Home” for Neuromuscular Disease Patients With Respiratory Tract Infection: A Pilot Study

“Hospital at Home” for Neuromuscular Disease Patients With Respiratory Tract Infection: A Pilot Study

Prognostic variables in newly diagnosed children and adolescents with acute myeloid leukemia: Children's Cancer Group Study 213

Monte Carlo Analysis in Academic Research

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