Likelihood approach for count data in longitudinal experiments

Gonçalves, Maria Helena; Cabral, M. Salomé; Villa, M.C. Ruíz de; Escrich, Eduard; Solanas, Montse

doi:10.1016/j.csda.2007.03.002

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…where the mean values θ t is related to the covariates by a logarithmic link function as in Equation 1, leading θ t = exp(x t β), we need that E(ε t ) = v t > 0, which is one peculiar feature of this model, see Gonçalves et al (2007) for details. In addition, negative autocorrelations are not allowed.…”

Section: Marginal Modelmentioning

confidence: 99%

“…, T i . The model is referred as random intercept model and has been developed by Gonçalves (2002) and Gonçalves et al (2007). Thus, for the random intercept model, if we consider…”

Section: Random Effects Modelmentioning

confidence: 99%

“…The method proposed by Azzalini (1994) is implemented in S-PLUS described by Azzalini and Chiogna (1997). Gonçalves (2002) and Gonçalves, Cabral, de Villa, Escrich, and Solanas (2007) developed the model proposed by Azzalini (1994) for Poisson response variables, where the serial dependence is assumed to be of Markovian type, through the inclusion of a random term in the linear predictor. Maximum likelihood estimation is used in both marginal and random effects models.…”

Section: Introductionmentioning

confidence: 99%

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cold: An R Package for the Analysis of Count Longitudinal Data

Gonçalves¹,

Cabral²

2021

J. Stat. Soft.

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This paper describes the R package cold for the analysis of count longitudinal data. In this package marginal and random effects models are considered. In both cases estimation is via maximization of the exact likelihood and serial dependence among observations is assumed to be of Markovian type and referred as the integer-valued autoregressive of order one process. For random effects models adaptive Gaussian quadrature and Monte Carlo methods are used to compute integrals whose dimension depends on the structure of random effects. cold is written partly in R language, partly in Fortran 77, interfaced through R and is built following the S4 formulation of R methods.

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Section: Marginal Modelmentioning

confidence: 99%

“…, T i . The model is referred as random intercept model and has been developed by Gonçalves (2002) and Gonçalves et al (2007). Thus, for the random intercept model, if we consider…”

Section: Random Effects Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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cold: An R Package for the Analysis of Count Longitudinal Data

Gonçalves¹,

Cabral²

2021

J. Stat. Soft.

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“…To study the effects of dietary lipids on experimental breast cancer, several clinical parameters have been defined, in addition to suitable statistical analysis (23)(24)(25)(26) . In sixteen experimental series developed in our laboratory, results have always been conclusive: diets with a high content of n-6 PUFA (corn oil) exert a clear stimulating effect of the experimental mammary carcinogenesis in all the clinical parameters studied (22,(27)(28)(29)(30)(31) (Fig.…”

Section: Effects Of Extra Virgin Olive Oil On Experimental Breast Canmentioning

confidence: 99%

Olive oil, an essential component of the Mediterranean diet, and breast cancer

Escrich

Moral

Solanas

2011

Public Health Nutr.

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Objective: The Mediterranean diet has been related to a lower risk of some chronic diseases, including cancer. We aim to gain insight into the effects of the main source of fat of this diet on breast cancer, the most common type of malignancy in women. Design: Data from sixteen experimental series analysing the effects of dietary lipids on mammary carcinogenesis in an animal model, in the context of the international literature on the Mediterranean diet, olive oil and breast cancer risk. Setting: Experimental and human data on the effects of olive oil and Mediterranean diet on breast cancer. Subjects: An animal model of induced breast cancer and other human and experimental studies in the literature.Results: Diets rich in extra virgin olive oil (EVOO) exert a negative modulatory effect on experimental breast cancer to a weak promoting effect, much lower than that obtained with a high-corn oil diet. EVOO confers to the mammary adenocarcinomas a clinical behaviour and morphological features compatible with low tumour aggressiveness. This differential effect, in relation to other dietary lipids, may be related to a lower effect on body weight and sexual maturation. In addition, EVOO induced different molecular changes in tumours, such as in the composition of cell membranes, activity of signalling proteins and gene expression. All these modifications could induce lower proliferation, higher apoptosis and lower DNA damage. These results, together with the favourable effect of olive oil reported in the literature when it is consumed in moderate quantities, suggest a beneficial influence of EVOO on breast cancer risk. Conclusions: Consumption of EVOO in moderate quantities and throughout the lifetime appears to be a healthy choice and may favourably influence breast cancer risk.

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Olive Oil and Other Dietary Lipids in Breast Cancer

Escrich

Solanas

Moral

2013

Advances in Nutrition and Cancer

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Breast cancer is the most frequent malignant neoplasia among women worldwide. In addition to genetic and endocrine factors, the environment, and specifically nutritional factors, plays a key role in its aetiology. Epidemiological and in particular experimental studies have shown the link between dietary fat and breast cancer. Abundant data have attributed a potentially chemopreventive effect for extra-virgin olive oil (EVOO), the main source of fat in the Mediterranean diet, which is associated with low incidence and mortality rates from chronic diseases such as breast cancer. We have demonstrated the differential modulatory effect of dietary lipids on mammary carcinogenesis, mainly in studies developed in an experimental model. Thus, diets high in n-6 polyunsaturated fatty acids (PUFA) have a clear stimulating influence, whereas EVOO diets mainly have a negative modulatory effect on breast cancer development. The specific mechanisms involved are not fully understood, but nowadays, it is widely accepted that they are numerous and complex. Our group has contributed to improving the knowledge of these mechanisms by demonstrating the influence of dietary lipids on the structure and function of cell membranes, the modulation of cell-signalling transduction pathways, the regulation of gene expression and growth and sexual maturity.

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Likelihood approach for count data in longitudinal experiments

Cited by 5 publications

References 9 publications

cold: An R Package for the Analysis of Count Longitudinal Data

cold: An R Package for the Analysis of Count Longitudinal Data

Olive oil, an essential component of the Mediterranean diet, and breast cancer

Olive Oil and Other Dietary Lipids in Breast Cancer

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