A Method for Computing Profile-Likelihood-Based Confidence Intervals

Venzon, David; Moolgavkar, Suresh H.

doi:10.2307/2347496

Cited by 475 publications

(385 citation statements)

References 14 publications

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“…Table 3 and Fig. 7, were computed using a numerical algorithm presented in [18]. The profile-based CIs, except CI α 7 , are rather close to the variance-covariance-based ones.…”

Section: Profile-likelihood-based Methodsmentioning

confidence: 86%

“…Profile-likelihood method provides a method for computing the confidence intervals of the maximum likelihood parameter estimates by following 'a global' behaviour of the objective function [18]. To compute approximations to the 95% CIs of the estimates, we proceed as follows.…”

Section: Profile-likelihood-based Methodsmentioning

confidence: 99%

“…We have performed computational analysis of the confidence intervals for the vector of 11 parameters (4.5) of the heterogenous model (3.1) with β j = 0, j = 0, 1, 2, 3, 6, 7, as fixed ad hoc. There exist three major approaches to evaluate CIs: the technique based on the variance-covariance matrix [4], the profilelikelihood-based method [18] and two variants of the bootstrap method -parametric and non-parametric ones [7]. We apply these methods and assess their relative performance by computing approximations to 95% confidence intervals for the estimated parameters.…”

Section: Confidence Of the Parameter Estimationmentioning

confidence: 99%

“…To compute the confidence intervals by the profile-likelihood-based method, we used an algorithm described in [18], which is based on a modified Newton-Raphson iteration to solve a system of equations that determines the lower and upper bounds of a CI. One bound is usually located by 4-10 iterations, depending on the requested accuracy and the quality of the starting point.…”

Section: Computational Performancementioning

confidence: 99%

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Computational analysis of CFSE proliferation assay

et al. 2006

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CFSE based tracking of the lymphocyte proliferation using flow cytometry is a powerful experimental technique in immunology allowing for the tracing of labelled cell populations over time in terms of the number of divisions cells undergone. Interpretation and understanding of such population data can be greatly improved through the use of mathematical modelling. We apply a heterogeneous linear compartmental model, described by a system of ordinary differential equations similar to those proposed by Kendall. This model allows division number-dependent rates of cell proliferation and death and describes the rate of changes in the numbers of cells having undergone j divisions. The experimental data set that we specifically analyze specifies the following characteristics of the kinetics of PHA-induced human T lymphocyte proliferation assay in vitro: (i) the total number of live cells, (ii) the total number of dead but not disintegrated cells and (iii) the number of cells divided j times. Following the maximum likelihood approach for data fitting, we estimate the model parameters which, in particular, present the CTL birth-and death rate "functions". It is the first study of CFSE labelling data which convincingly shows that the lymphocyte proliferation and death both in vitro and in vivo are division number dependent. For the first time, the confidence in the estimated parameter values is analyzed by comparing three major methods: the technique based on the variance-covariance matrix, the profile-likelihood-based approach and the bootstrap technique. We compare results and performance of these methods with respect to their robustness and computational cost. We show that for evaluating mathematical models of differing complexity the information-theoretic approach, based upon indicators measuring the information loss for a particular model (Kullback-Leibler information), provides a consistent basis. We specifically discuss methodological and computational difficulties in parameter identification with CFSE data, e.g., the loss of confidence in the parameter estimates starting around the 6-th division. Overall, our study suggests that the heterogeneity inherent in cell kinetics should be explicitly incorporated into the structure of mathematical models.

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“…Table 3 and Fig. 7, were computed using a numerical algorithm presented in [18]. The profile-based CIs, except CI α 7 , are rather close to the variance-covariance-based ones.…”

Section: Profile-likelihood-based Methodsmentioning

confidence: 86%

Section: Profile-likelihood-based Methodsmentioning

confidence: 99%

Section: Confidence Of the Parameter Estimationmentioning

confidence: 99%

Section: Computational Performancementioning

confidence: 99%

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Computational analysis of CFSE proliferation assay

et al. 2006

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“…Minimizing the negative log of the likelihood is equivalent to maximizing the likelihood. Then, a profile-likelihood-based 95% confidence interval was obtained for the estimate μ (described in Venzon and Moolgavkar 1988). The mean and its confidence interval were converted back to representations of frequency, and, thus, an estimate of the 75% threshold point was obtained.…”

Section: Resultsmentioning

confidence: 99%

Discrimination of Schroeder-Phase Harmonic Complexes by Normal-Hearing and Cochlear-Implant Listeners

Drennan

Longnion

Ruffin

et al. 2007

JARO

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The temporal fine structure (TFS) of sound contributes significantly to the perception of music and speech in noise. The evaluation of new strategies to improve TFS delivery in cochlear implants (CIs) relies upon the assessment of fine structure encoding. Most modern CI sound processing schemes do not encode withinchannel TFS per se, but some TFS information is delivered through temporal envelope cues across multiple channels. Positive and negative Schroeder-phase harmonic complexes differ primarily in acoustic TFS and provide a potential test of TFS discrimination ability in CI users for current and future processing strategies. The ability to discriminate Schroeder-phase stimuli was evaluated in 24 CI users and 7 normal-hearing listeners at four fundamental frequencies: 50, 100, 200, and 400 Hz. The dependent variables were percent correct at each fundamental frequency, average score across all fundamental frequencies, and a maximum-likelihoodpredicted threshold fundamental frequency for 75% correct. CI listeners scored better than chance for all fundamental frequencies tested. The 50-Hz, average, and predicted threshold scores correlated significantly with consonant-nucleus-consonant word scores. The 200-Hz score correlated with a measure of speech perception in speech-shaped noise. Pitch-direction sensitivity is predicted jointly by the 400-Hz Schroeder score and a spectral ripple discrimination task. The results demonstrate that the Schroeder test is a potentially useful measure of clinically relevant temporal processing abilities in CI users.

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Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City

et al. 2020

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IMPORTANCE Black and Hispanic populations have higher rates of coronavirus disease 2019 hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. OBJECTIVETo compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status.EXPOSURES Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). MAIN OUTCOMES AND MEASURESThe likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). RESULTSAmong 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). CONCLUSIONS AND RELEVANCEIn this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have (continued) Key Points Question Do outcomes among patients with coronavirus disease 2019 (COVID-19) differ by race/ethnicity, and are observed disparities associated with comorbidity and neighborhood characteristics? Findings This cohort study including ...

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A Method for Computing Profile-Likelihood-Based Confidence Intervals

Cited by 475 publications

References 14 publications

Computational analysis of CFSE proliferation assay

Computational analysis of CFSE proliferation assay

Discrimination of Schroeder-Phase Harmonic Complexes by Normal-Hearing and Cochlear-Implant Listeners

Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City

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