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  1. Article ; Online: Practice Variation in Vena Cava Filter Use Among Trauma Centers in the National Trauma Database.

    Gilligan, Timothy C / Cook, Alan D / Hosmer, David W / Hunter, Drew C / Vernon, Tawnya M / Weinberg, Jordan A / Ward, Jeanette / Rogers, Frederick B

    The Journal of surgical research

    2019  Volume 246, Page(s) 145–152

    Abstract: Background: Agreement regarding indications for vena cava filter (VCF) utilization in trauma patients has been in flux since the filter's introduction. As VCF technology and practice guidelines have evolved, the use of VCF in trauma patients has changed. ...

    Abstract Background: Agreement regarding indications for vena cava filter (VCF) utilization in trauma patients has been in flux since the filter's introduction. As VCF technology and practice guidelines have evolved, the use of VCF in trauma patients has changed. This study examines variation in VCF placement among trauma centers.
    Materials and methods: A retrospective study was performed using data from the National Trauma Data Bank (2005-2014). Trauma centers were grouped according to whether they placed VCFs during the study period (VCF+/VCF-). A multivariable probit regression model was fit to predict the number of VCFs used among the VCF+ centers (the expected [E] number of VCF per center). The ratio of observed VCF placement (O) to expected VCFs (O:E) was computed and rank ordered to compare interfacility practice variation.
    Results: In total, 65,482 VCFs were placed by 448 centers. Twenty centers (4.3%) placed no VCFs. The greatest predictors of VCF placement were deep vein thrombosis, spinal cord paralysis, and major procedure. The strongest negative predictor of VCF placement was admission during the year 2014. Among the VCF+ centers, O:E varied by nearly 500%. One hundred fifty centers had an O:E greater than one. One hundred sixty-nine centers had an O:E less than one.
    Conclusions: Substantial variation in practice is present in VCF placement. This variation cannot be explained only by the characteristics of the patients treated at these centers but could be also due to conflicting guidelines, changing evidence, decreasing reimbursement rates, or the culture of trauma centers.
    MeSH term(s) Adolescent ; Adult ; Databases, Factual/statistics & numerical data ; Equipment and Supplies Utilization/economics ; Equipment and Supplies Utilization/standards ; Equipment and Supplies Utilization/statistics & numerical data ; Female ; Humans ; Male ; Middle Aged ; Practice Guidelines as Topic ; Practice Patterns, Physicians'/standards ; Practice Patterns, Physicians'/statistics & numerical data ; Pulmonary Embolism/etiology ; Pulmonary Embolism/prevention & control ; Reimbursement Mechanisms/standards ; Reimbursement Mechanisms/statistics & numerical data ; Retrospective Studies ; Risk Factors ; Time Factors ; Trauma Centers/economics ; Trauma Centers/standards ; Trauma Centers/statistics & numerical data ; Vena Cava Filters/economics ; Vena Cava Filters/statistics & numerical data ; Venous Thrombosis/etiology ; Venous Thrombosis/prevention & control ; Wounds and Injuries/complications ; Wounds and Injuries/therapy ; Young Adult
    Language English
    Publishing date 2019-09-30
    Publishing country United States
    Document type Comparative Study ; Journal Article
    ZDB-ID 80170-7
    ISSN 1095-8673 ; 0022-4804
    ISSN (online) 1095-8673
    ISSN 0022-4804
    DOI 10.1016/j.jss.2019.09.004
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Distance of response to host tree models by female apple maggot flies,Rhagoletis pomonella (Walsh) (Diptera: Tephritidae): Interaction of visual and olfactory stimuli.

    Green, T A / Prokopy, R J / Hosmer, D W

    Journal of chemical ecology

    2013  Volume 20, Issue 9, Page(s) 2393–2413

    Abstract: Mature female apple maggot flies,Rhagoletis pomonella (Walsh), were released individually onto a single potted, fruitless hawthorne tree in the center of an open field. The tree was surrounded by four 1-m(2) plywood host tree models painted green or ... ...

    Abstract Mature female apple maggot flies,Rhagoletis pomonella (Walsh), were released individually onto a single potted, fruitless hawthorne tree in the center of an open field. The tree was surrounded by four 1-m(2) plywood host tree models painted green or white, with or without synthetic host fruit odor (butyl hexanoate), and placed at one of several distances from the release tree. Each fly was permitted to forage freely on the release tree for up to 1 hr, or until it left the tree. Flies left the tree significantly sooner when green models with host fruit were present at 0.5, 1.5, or 2.5 m distance from the release tree than when these models were placed at a greater distance (4.5 m) from the release tree or when no models were present. Flies responded detectably to 1-m(2) models without odor up to a maximum distance of 1.5 m. These results suggest that female apple maggot flies did not detect green 1-m(2) models with odor 4.5 m away or models without odor 2.5 m or more away. Flies responded to white models with and without odor to a much lesser extent, both in terms of response distance and flight to and alightment upon models. Increasing model size to 2 m(2) increased the distance to 2.5 m at which flies responded to green models without odor. Decreasing model size to 0.5 m(2) reduced fly responsiveness to green or white models. The presence of host fruit odor alone, without the visual stimulus of a green model, did not influence residence time on the release tree.
    Language English
    Publishing date 2013-11-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 800130-3
    ISSN 1573-1561 ; 0098-0331
    ISSN (online) 1573-1561
    ISSN 0098-0331
    DOI 10.1007/BF02033209
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Multivariable Model‐building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables by ROYSTON, P. and SAUERBREI, W

    Hosmer, David W

    Biometrics. 2009 Sept., v. 65, no. 3

    2009  

    Abstract: ... Polynomials for Modelling Continuous Variables (P. Royston and W. Sauerbrei) David W. Hosmer Modern ... Random Effect and Latent Variable Model Selection (D. B. Dunson, Editor) Kenneth Rice Missing Data ... Statistics (S. Dabo‐Niang and F. Ferraty, Editors) Jason D. Nielsen Statistical Analysis and Modelling ...

    Abstract Multivariable Model‐building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables (P. Royston and W. Sauerbrei) David W. Hosmer Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning (A. J. Izenman) Debashis Ghosh A Primer on Linear Models (J. F. Monahan) Muni S. Srivastava Mixed Effects Models and Extensions in Ecology with R (A. F. Zuur, E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith) Carl James Schwarz Random Effect and Latent Variable Model Selection (D. B. Dunson, Editor) Kenneth Rice Missing Data in Clinical Studies (G. Molenberghs and M. G. Kenward) Suzanne R. Dubnicka Functional and Operatorial Statistics (S. Dabo‐Niang and F. Ferraty, Editors) Jason D. Nielsen Statistical Analysis and Modelling of Spatial Point Patterns (J. Illian, A. Penttinen, H. Stoyan, and D. Stoyan) Jesper Møller Solved Problem in Geostatistics (O. Leuangthong, K. D. Khan, and C. V. Deutsch) Ole F. Christensen Statistical Methods for Environmental Epidemiology with R: A Case Study in Air Pollution and Health (R. D. Peng and F. Dominici) David Buckeridge Correspondence Analysis in Practice, Second Edition (M. Greenacre) Willem Heiser Introduction to Statistical Mediation Analysis (D. P. MacKinnon) Tyler J. VanderWeele Brief Reports by the Editor The EM Algorithm and Extensions, 2nd edition (G. J. McLachlan and T. Krishnan) Probability Models for DNA Sequence Evolution, 2nd edition (R. Durrett) Bayesian Methods for Data Analysis, 3rd edition (B. P. Carlin and T. A. Louis) Nonlinear Regression with R (C. Ritz and J. C. Streibig) Cancer Mortality and Morbidity Patterns in the U.S. Population: An Interdisciplinary Approach (K. G. Manton, I. Akushevich, and J. Kravchenko)
    Keywords models ; biometry ; geostatistics ; nucleotide sequences ; clinical trials ; regression analysis ; air pollution ; epidemiology ; DNA ; algorithms ; mortality ; case studies ; learning ; statistics ; statistical analysis ; morbidity ; mathematical models ; probability ; linear models ; correspondence analysis ; ecology ; United States ; evolution
    Language English
    Dates of publication 2009-09
    Size p. 989-990.
    Publishing place Blackwell Publishing Inc
    Document type Article
    ZDB-ID 213543-7
    ISSN 0099-4987 ; 0006-341X
    ISSN 0099-4987 ; 0006-341X
    DOI 10.1111/j.1541-0420.2009.01315_1.x
    Database NAL-Catalogue (AGRICOLA)

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  4. Article ; Online: Failure to get into substance abuse treatment.

    Fisher, Dennis G / Reynolds, Grace L / D'Anna, Laura H / Hosmer, David W / Hardan-Khalil, Kholoud

    Journal of substance abuse treatment

    2017  Volume 73, Page(s) 55–62

    Abstract: Among substance abusers in the US, the discrepancy in the number who access substance abuse treatment and the number who need treatment is sizable. This results in a major public health problem of access to treatment. The purpose of this study was to ... ...

    Abstract Among substance abusers in the US, the discrepancy in the number who access substance abuse treatment and the number who need treatment is sizable. This results in a major public health problem of access to treatment. The purpose of this study was to examine characteristics of Persons Who Use Drugs (PWUDs) that either hinder or facilitate access to treatment. 2646 participants were administered the Risk Behavior Assessment (RBA) and the Barratt Impulsiveness Scale. The RBA included the dependent variable which was responses to the question "During the last year, have you ever tried, but been unable, to get into a drug treatment or detox program?" In multivariate analysis, factors associated with being unable to access treatment included: Previously been in drug treatment (OR=4.51), number of days taken amphetamines in the last 30days (OR=1.18), traded sex for drugs (OR=1.53), homeless (OR=1.73), Nonplanning subscale of the Barratt Impulsiveness Scale (OR=1.19), age at interview (OR=0.91), and sexual orientation, with bisexual men and women significantly more likely than heterosexuals to have tried but been unable to get into treatment. The answers to the question on "why were you unable to get into treatment" included: No room, waiting list; not enough money, did not qualify, got appointment but no follow through, still using drugs, and went to jail before program start. As expected, findings suggest that limiting organizational and financial obstacles to treatment may go a long way in increasing drug abuse treatment accessibility to individuals in need. Additionally, our study points to the importance of developing approaches for increasing personal planning skills/reducing Nonplanning impulsivity among PWUDs when they are in treatment as a key strategy to ensure access to additional substance abuse treatment in the future.
    Language English
    Publishing date 2017-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 605923-5
    ISSN 1873-6483 ; 0740-5472
    ISSN (online) 1873-6483
    ISSN 0740-5472
    DOI 10.1016/j.jsat.2016.11.004
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: The log multinomial regression model for nominal outcomes with more than two attributes.

    Blizzard, L / Hosmer, D W

    Biometrical journal. Biometrische Zeitschrift

    2007  Volume 49, Issue 6, Page(s) 889–902

    Abstract: An estimate of the risk or prevalence ratio, adjusted for confounders, can be obtained from a log binomial model (binomial errors, log link) fitted to binary outcome data. We propose a modification of the log binomial model to obtain relative risk ... ...

    Abstract An estimate of the risk or prevalence ratio, adjusted for confounders, can be obtained from a log binomial model (binomial errors, log link) fitted to binary outcome data. We propose a modification of the log binomial model to obtain relative risk estimates for nominal outcomes with more than two attributes (the "log multinomial model"). Extensive data simulations were undertaken to compare the performance of the log multinomial model with that of an expanded data multinomial logistic regression method based on the approach proposed by Schouten et al. (1993) for binary data, and with that of separate fits of a Poisson regression model based on the approach proposed by Zou (2004) and Carter, Lipsitz and Tilley (2005) for binary data. Log multinomial regression resulted in "inadmissable" solutions (out-of-bounds probabilities) exceeding 50% in some data settings. Coefficient estimates by the alternative methods produced out-of-bounds probabilities for the log multinomial model in up to 27% of samples to which a log multinomial model had been successfully fitted. The log multinomial coefficient estimates generally had lesser relative bias and mean squared error than the alternative methods. The practical utility of the log multinomial regression model was demonstrated with a real data example. The log multinomial model offers a practical solution to the problem of obtaining adjusted estimates of the risk ratio in the multinomial setting, but must be used with some care and attention to detail.
    MeSH term(s) Child ; Computer Simulation ; Humans ; Logistic Models ; Male ; Models, Statistical ; Odds Ratio ; Smoking
    Language English
    Publishing date 2007-12
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 131640-0
    ISSN 1521-4036 ; 0323-3847 ; 0006-3452
    ISSN (online) 1521-4036
    ISSN 0323-3847 ; 0006-3452
    DOI 10.1002/bimj.200610377
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Parameter estimation and goodness-of-fit in log binomial regression.

    Blizzard, L / Hosmer, D W

    Biometrical journal. Biometrische Zeitschrift

    2006  Volume 48, Issue 1, Page(s) 5–22

    Abstract: An estimate of the risk, adjusted for confounders, can be obtained from a fitted logistic regression model, but it substantially over-estimates when the outcome is not rare. The log binomial model, binomial errors and log link, is increasingly being used ...

    Abstract An estimate of the risk, adjusted for confounders, can be obtained from a fitted logistic regression model, but it substantially over-estimates when the outcome is not rare. The log binomial model, binomial errors and log link, is increasingly being used for this purpose. However this model's performance, goodness of fit tests and case-wise diagnostics have not been studied. Extensive simulations are used to compare the performance of the log binomial, a logistic regression based method proposed by Schouten et al. (1993) and a Poisson regression approach proposed by Zou (2004) and Carter, Lipsitz, and Tilley (2005). Log binomial regression resulted in "failure" rates (non-convergence, out-of-bounds predicted probabilities) as high as 59%. Estimates by the method of Schouten et al. (1993) produced fitted log binomial probabilities greater than unity in up to 19% of samples to which a log binomial model had been successfully fit and in up to 78% of samples when the log binomial model fit failed. Similar percentages were observed for the Poisson regression approach. Coefficient and standard error estimates from the three models were similar. Rejection rates for goodness of fit tests for log binomial fit were around 5%. Power of goodness of fit tests was modest when an incorrect logistic regression model was fit. Examples demonstrate the use of the methods. Uncritical use of the log binomial regression model is not recommended.
    MeSH term(s) Algorithms ; Biometry/methods ; Computer Simulation ; Data Interpretation, Statistical ; Linear Models ; Logistic Models ; Models, Biological ; Numerical Analysis, Computer-Assisted ; Proportional Hazards Models ; Regression Analysis
    Language English
    Publishing date 2006-03-08
    Publishing country Germany
    Document type Evaluation Studies ; Journal Article
    ZDB-ID 131640-0
    ISSN 1521-4036 ; 0323-3847 ; 0006-3452
    ISSN (online) 1521-4036
    ISSN 0323-3847 ; 0006-3452
    DOI 10.1002/bimj.200410165
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Canary, Jana D / Blizzard, Leigh / Barry, Ronald P / Hosmer, David W / Quinn, Stephen J

    Biometrical journal. Biometrische Zeitschrift

    2015  Volume 58, Issue 3, Page(s) 674–690

    Abstract: ... any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J ...

    Abstract Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) .
    MeSH term(s) Biometry/methods ; Computer Simulation ; Data Interpretation, Statistical ; Humans ; Linear Models ; Models, Statistical
    Language English
    Publishing date 2015-11-19
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 131640-0
    ISSN 1521-4036 ; 0323-3847 ; 0006-3452
    ISSN (online) 1521-4036
    ISSN 0323-3847 ; 0006-3452
    DOI 10.1002/bimj.201400079
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Assessment of periphyton, aquatic macrophytes, benthic communities, and physical habitat in midwestern United States streams coinciding with varying historical concentrations of atrazine.

    Hall, Lenwood W / Anderson, Ronald D / Killen, William D / Hosmer, Alan J / Brain, Richard A

    Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering

    2014  Volume 49, Issue 10, Page(s) 1091–1099

    Abstract: The objectives of this pilot study were to: (1) characterize periphyton and benthic communities using standard collection methods in six Midwest watersheds with varying historical levels of atrazine (low range, medium range and upper range); (2) ... ...

    Abstract The objectives of this pilot study were to: (1) characterize periphyton and benthic communities using standard collection methods in six Midwest watersheds with varying historical levels of atrazine (low range, medium range and upper range); (2) qualitatively assess presence of aquatic vascular plants at each site; (3) assess and compare physical habitat at each study site in order to evaluate how physical habitat structure may influence the biological communities and (4) analyze the periphyton and benthic macroinvertebrate community data (i.e., series of metrics) among sites to evaluate possible differences or similarities among sites with different historical atrazine exposures. Five of the eight physical habitat metrics (including total physical habitat score) were different among the six study sites. There appeared to be no substantial difference in the structure of periphtyon communities at the six Midwest sites based on 9 of 12 metrics. For the three metrics that showed differences among sites-percentage of sensitive diatoms, percent Achnanches minutissima and percent motile diatoms - there was no consistent pattern with previous degrees of atrazine exposure and the scoring of these metrics. There were also no statistical differences in aquatic macrophyte spatial coverage among the six study areas. Thus, based on the spatially and temporally limited periphyton and aquatic macrophyte data, varying historical atrazine exposure was not associated with impact on resident plant communities (the target receptor group for atrazine). All 10 benthic community metrics showed significant differences among the six Midwest sites. Although no consistent pattern existed with varying historic levels of atrazine, benthic communities at one site with lower historical levels of atrazine were of higher quality than the other five sites. However, this one site also had a higher quality habitat compared to the other sites which was most likely the reason for this benthic condition.
    MeSH term(s) Animals ; Atrazine/analysis ; Diatoms ; Ecosystem ; Environmental Monitoring ; Herbicides/analysis ; Invertebrates ; Midwestern United States ; Pilot Projects ; Plants ; Rivers/chemistry
    Chemical Substances Herbicides ; Atrazine (QJA9M5H4IM)
    Language English
    Publishing date 2014
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 196584-0
    ISSN 1532-4117 ; 0360-1226 ; 1077-1204 ; 1093-4529
    ISSN (online) 1532-4117
    ISSN 0360-1226 ; 1077-1204 ; 1093-4529
    DOI 10.1080/10934529.2014.897143
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Variation in readmission rates among hospitals following admission for traumatic injury.

    Osler, Turner / Yuan, Dekang / Holden, Jeremy / Huang, Zihao / Cook, Alan / Glance, Laurent G / Buzas, Jeffrey S / Hosmer, David W

    Injury

    2018  Volume 50, Issue 1, Page(s) 173–177

    Abstract: Introduction: Readmission following hospital discharge is both common and costly. The Hospital Readmission Reduction Program (HRRP) financially penalizes hospitals for readmission following admission for some conditions, but this approach may not be ... ...

    Abstract Introduction: Readmission following hospital discharge is both common and costly. The Hospital Readmission Reduction Program (HRRP) financially penalizes hospitals for readmission following admission for some conditions, but this approach may not be appropriate for all conditions. We wished to determine if hospitals differed in their adjusted readmission rates following an index hospital admission for traumatic injury.
    Patients and methods: We extracted from the AHRQ National Readmission Dataset (NRD) all non-elderly adult patients hospitalized following traumatic injury in 2014. We estimated hierarchal logistic regression models to predicted readmission within 30 days. Models included either patient level predictors, hospital level predictors, or both. We quantified the extent of hospital variability in readmissions using the median odds ratio. Additionally, we computed hospital specific risk-adjusted rates of readmission and number of excess readmissions.
    Results: Of the 177,322 patients admitted for traumatic injury 11,940 (6.7%) were readmitted within 30 days. Unadjusted hospital readmission rates for the 637 hospitals in our study varied from 0% to 20%. After controlling for sources of variability the range for hospital readmission rates was between 5.5% and 8.5%. Only 2% of hospitals had a random intercept coefficient significantly different from zero, suggesting that their readmission rates differed from the mean level of all hospitals. We also estimated that in 2014 only 11% of hospitals had more than 2 excess readmissions. Our multilevel model discriminated patients who were readmitted from those not readmitted at an acceptable level (C = 0.74).
    Conclusions: We found little evidence that hospitals differ in their readmission rates following an index admission for traumatic injury. There is little justification for penalizing hospitals based on readmissions after traumatic injury.
    MeSH term(s) Adult ; Decision Making, Organizational ; Female ; Health Care Surveys ; Hospitalization/statistics & numerical data ; Hospitals ; Humans ; Logistic Models ; Male ; Medicare/economics ; Middle Aged ; Organizational Objectives ; Outcome Assessment (Health Care) ; Patient Discharge/economics ; Patient Discharge/statistics & numerical data ; Patient Readmission/economics ; Patient Readmission/statistics & numerical data ; Process Assessment (Health Care) ; Quality of Health Care ; United States ; Wounds and Injuries/economics ; Wounds and Injuries/epidemiology ; Wounds and Injuries/therapy
    Language English
    Publishing date 2018-08-27
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 218778-4
    ISSN 1879-0267 ; 0020-1383
    ISSN (online) 1879-0267
    ISSN 0020-1383
    DOI 10.1016/j.injury.2018.08.021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Empirical comparisons of proportional hazards, Poisson, and logistic regression modeling of occupational cohort data

    Hosmer, D. W.

    American J. Industrial Medicine

    1998  Volume 33, Issue 1, Page(s) 33–47

    Abstract: This research was conducted to examine the effect of model choice on the epidemiologic interpretation of occupational cohort data. Three multiplicative models commonly employed in the analysis of occupational cohort studies - proportional hazards, ... ...

    Institution USA-Burlington, VT 05405 Biometry Facility, Hills Building, University of Vermont College of Medicine
    Abstract This research was conducted to examine the effect of model choice on the epidemiologic interpretation of occupational cohort data. Three multiplicative models commonly employed in the analysis of occupational cohort studies - proportional hazards, Poisson, and logistic regression - were used to analyze data from an historical cohort study of workers exposed to formaldehyde. Samples were taken from this dataset to create a number of predetermined scenarios for comparing the models, varying study size, outcome frequency, strength of risk factors, and follow-up length. The Poisson and proportional hazards models yielded nearly identical relative risk estimates and confidence intervals in all situations except when confounding by age could not be closely controlled in the Poisson analysis. Logistic regression findings were more variable, with risk estimates differing most from the proportional hazards results when there was a common outcome or strong relative risk. The logistic model also provided less precise estimates than the other two. Thus, although logistic was the easiest model to implement, it should be used only in occupational cohort studies when the outcome is rare (5% or less), and the relative risk is less than ca. 2. Even then, the proportional hazards and Poisson models are better choices. Selecting between these two can be based on convenience in most circumstances.
    Keywords Kohortenstudie ; Epidemiologie ; Modell mathematisch ; Analyse ; Risiko ; Vergiftung ; Arbeitnehmer ; Formaldehyd ; Exposition
    Language English
    Document type Article
    ZDB-ID 604538-8
    ISSN 1097-0274 ; 0271-3586
    ISSN (online) 1097-0274
    ISSN 0271-3586
    Database Social Medicine (SOMED)

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