Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques

Laird, Nan M.; Olivier, Donald C.

doi:10.1080/01621459.1981.10477634

Cited by 411 publications

(130 citation statements)

References 10 publications

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“…This method is equivalent to the Cox regression under the assumption of piecewise constant incident rates (Andersen et al 1993; Laird & Olivier 1981). The exponentiated estimate in a Poisson regression is the incidence rate ratio (IRR).…”

Section: Methodsmentioning

confidence: 99%

Parental history of psychiatric diagnoses and unipolar depression: a Danish National Register-based cohort study

et al. 2015

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Background Depression is known to run in families, but the effects of parental history of other psychiatric diagnoses on depression rates are less well studied. Few studies have examined the impact of parental psychopathology on depression rates in older age groups. Methods We established a population-based cohort including all individuals born in Denmark after 1954 and alive on their 10th birthday (N=2,976,264). Exposure variables were maternal and paternal history of schizophrenia, bipolar disorder, depression, anxiety or ‘other’ psychiatric diagnoses. Incidence rate ratios (IRR) were estimated using poisson regressions. Results Parental history of any psychiatric diagnosis increased incidence rates of outpatient (maternal: IRR = 1.88, p < .0001; paternal: IRR = 1.68, p < .0001) and inpatient (maternal: IRR = 1.99, p < .0001; paternal: IRR = 1.83, p < .0001) depression relative to no parental history. IRRs for parental history of non-affective disorders remained relatively stable across age groups, while IRRs for parental affective disorders (unipolar or bipolar) decreased with age from 2.29–3.96 in the youngest age group to 1.53–1.90 in the oldest group. IRR estimates for all parental diagnoses were similar among individuals 41+ (IRR range: 1.51–1.90). Conclusions Parental history of any psychiatric diagnosis is associated with increased incidence rates of unipolar depression. In younger age groups, parental history of affective diagnoses is more strongly associated with rates of unipolar depression than non-affective diagnoses, however this distinction disappears after age 40, suggesting that parental psychopathology in general, rather than any one disorder, confers risk for depression in middle life.

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Section: Methodsmentioning

confidence: 99%

Parental history of psychiatric diagnoses and unipolar depression: a Danish National Register-based cohort study

et al. 2015

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“…Some authors have considered random cutpoints (see, e.g., Sahu and Dey, 2004). Regardless, the resulting model implies a Poisson likelihood (Laird and Olivier, 1981) as follows. Let K ( t ) = min{ k : a k ≥ t }, Δ k ( t ) = min{ a k , t } − a k −1 , and y ijk = δ ij I { k = K ( t ij )}.…”

Section: The Proposalmentioning

confidence: 99%

Modeling county level breast cancer survival data using a covariate-adjusted frailty proportional hazards model

Zhou¹,

Hanson²,

Jara³

et al. 2015

Ann. Appl. Stat.

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Understanding the factors that explain differences in survival times is an important issue for establishing policies to improve national health systems. Motivated by breast cancer data arising from the Surveillance Epidemiology and End Results program, we propose a covariate-adjusted proportional hazards frailty model for the analysis of clustered right-censored data. Rather than incorporating exchangeable frailties in the linear predictor of commonly-used survival models, we allow the frailty distribution to flexibly change with both continuous and categorical cluster-level covariates and model them using a dependent Bayesian nonparametric model. The resulting process is flexible and easy to fit using an existing R package. The application of the model to our motivating example showed that, contrary to intuition, those diagnosed during a period of time in the 1990s in more rural and less affluent Iowan counties survived breast cancer better. Additional analyses showed the opposite trend for earlier time windows. We conjecture that this anomaly has to be due to increased hormone replacement therapy treatments prescribed to more urban and affluent subpopulations.

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“…For example, in Catalonia for the year 2007, the Catalan Institute of Medical and Health Evaluations (ICAMS, by its Spanish acronym) recorded 800,464 sickness episodes in 580,959 persons. It is well established that Poisson regression is a possible alternative to Cox regression [13,14]. Specifically, when a Cox model is confronted with computational limitations in analyzing large databases, a Poisson regression model maybe a reasonable alternative [15].…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity and event dependence in the analysis of sickness absence

Torà-Rocamora

Gimeno

Delclos

et al. 2013

BMC Med Res Methodol

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BackgroundSickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration.MethodsTo overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders.ResultsAs expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM.ConclusionsThe CFPM is an suitable alternative to the CFM in survival analysis with recurrent events, especially with large databases.

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Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques

Cited by 411 publications

References 10 publications

Parental history of psychiatric diagnoses and unipolar depression: a Danish National Register-based cohort study

Parental history of psychiatric diagnoses and unipolar depression: a Danish National Register-based cohort study

Modeling county level breast cancer survival data using a covariate-adjusted frailty proportional hazards model

Heterogeneity and event dependence in the analysis of sickness absence

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