Smoothing grouped bivariate data to obtain the incubation period distribution of AIDS. 1994

J M Taylor, and Y Chon
Department of Biostatistics, UCLA School of Public Health 90024.

We use a penalized likelihood approach to obtain a smooth estimate of a bivariate distribution from grouped data where each observation consists of a region in a plane. The purpose of the analysis is to estimate the incubation period distribution of AIDS from the Multicenter AIDS Cohort Study, a prevalent cohort of homosexual men. In this article we illustrate the usefulness of the penalized likelihood approach. We also discuss the use of a cross-validation and a Bayesian scheme to choose the smoothing parameters and bootstrap samples to assess uncertainty.

UI MeSH Term Description Entries
D008297 Male Males
D004196 Disease Outbreaks Sudden increase in the incidence of a disease. The concept includes EPIDEMICS and PANDEMICS. Outbreaks,Infectious Disease Outbreaks,Disease Outbreak,Disease Outbreak, Infectious,Disease Outbreaks, Infectious,Infectious Disease Outbreak,Outbreak, Disease,Outbreak, Infectious Disease,Outbreaks, Disease,Outbreaks, Infectious Disease
D005500 Follow-Up Studies Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease. Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup
D006716 Homosexuality The sexual attraction or relationship between members of the same SEX. Homosexuality, Ego-Dystonic,Ego-Dystonic Homosexuality,Homosexuality, Ego Dystonic
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000163 Acquired Immunodeficiency Syndrome An acquired defect of cellular immunity associated with infection by the human immunodeficiency virus (HIV), a CD4-positive T-lymphocyte count under 200 cells/microliter or less than 14% of total lymphocytes, and increased susceptibility to opportunistic infections and malignant neoplasms. Clinical manifestations also include emaciation (wasting) and dementia. These elements reflect criteria for AIDS as defined by the CDC in 1993. AIDS,Immunodeficiency Syndrome, Acquired,Immunologic Deficiency Syndrome, Acquired,Acquired Immune Deficiency Syndrome,Acquired Immuno-Deficiency Syndrome,Acquired Immuno Deficiency Syndrome,Acquired Immuno-Deficiency Syndromes,Acquired Immunodeficiency Syndromes,Immuno-Deficiency Syndrome, Acquired,Immuno-Deficiency Syndromes, Acquired,Immunodeficiency Syndromes, Acquired,Syndrome, Acquired Immuno-Deficiency,Syndrome, Acquired Immunodeficiency,Syndromes, Acquired Immuno-Deficiency,Syndromes, Acquired Immunodeficiency
D015141 Los Angeles City in California.
D015203 Reproducibility of Results The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results. Reliability and Validity,Reliability of Result,Reproducibility Of Result,Reproducibility of Finding,Validity of Result,Validity of Results,Face Validity,Reliability (Epidemiology),Reliability of Results,Reproducibility of Findings,Test-Retest Reliability,Validity (Epidemiology),Finding Reproducibilities,Finding Reproducibility,Of Result, Reproducibility,Of Results, Reproducibility,Reliabilities, Test-Retest,Reliability, Test-Retest,Result Reliabilities,Result Reliability,Result Validities,Result Validity,Result, Reproducibility Of,Results, Reproducibility Of,Test Retest Reliability,Validity and Reliability,Validity, Face
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D015331 Cohort Studies Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or other outcome. Cohorts are defined populations which, as a whole, are followed in an attempt to determine distinguishing subgroup characteristics. Birth Cohort Studies,Birth Cohort Study,Closed Cohort Studies,Cohort Analysis,Concurrent Studies,Historical Cohort Studies,Incidence Studies,Analysis, Cohort,Cohort Studies, Closed,Cohort Studies, Historical,Studies, Closed Cohort,Studies, Concurrent,Studies, Historical Cohort,Analyses, Cohort,Closed Cohort Study,Cohort Analyses,Cohort Studies, Birth,Cohort Study,Cohort Study, Birth,Cohort Study, Closed,Cohort Study, Historical,Concurrent Study,Historical Cohort Study,Incidence Study,Studies, Birth Cohort,Studies, Cohort,Studies, Incidence,Study, Birth Cohort,Study, Closed Cohort,Study, Cohort,Study, Concurrent,Study, Historical Cohort,Study, Incidence

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