Evaluation of the thermoregulatory response of goats naturally exposed to the tropical climate using longitudinal data / Avaliação da resposta termorregulatória de cabras expostas naturalmente ao clima tropical a partir do uso de dados longitudinais

Rectal temperature (RT), heart rate (HR), and respiratory rate (RR), determined as repeated measurements over time in female goats, were used to identify covariance matrices that best fit the data for residual modeling on these three traits. Then, based on this result, the goats' responses to heat were evaluated. Five matrices were found with convergence for the three traits. The Heterogeneous Compound Symmetry matrix showed a good fit for modeling the residual associated with RT, whereas the Heterogeneous Autoregressive matrix had a better fit for RR and HR, according to the Akaike Information Criteria (AIC), corrected AIC (AICc), and Schwarz Bayesian Information Criterion (BIC) used. After adjusting the residual data for these three traits, a mixed-model analysis was used to evaluate collection period (3), physiological stage (3), and animal age (3) as fixed effects. Residual modeling interfered differently with the p-value associated with the fixed effects studied. Collection period and interactions did not influence the variation in RT (P>0.761), which was within the standard range for goats in the tropics, while the physiological stage of the goats affected it (P<0.05). Rectal temperature, HR, and RR tend to show covariance structures that can be modeled using specific residual covariance matrices, that is, the heterogeneous compound symmetry matrix best suits RT data, whereas the heterogeneous autoregressive matrix is better suited for HR and RR, which are usually correlated. The goats of the evaluated breed maintain RT within the range of variation displayed by breeds adapted to a hot environment, regardless of their physiological condition. Variations occur in RR and HR, without, however, exceeding the normal range for goats. Pregnancy causes goats to raise their RR in the rainy season of the year in the region in order to maintain RT within the normal range for the species.(AU)

Utilizou-se a Temperatura retal (TR), Frequências cardíaca (FC) e respiratória (FR) aferidas como medidas repetidas no tempo em fêmeas caprinas, objetivando-se identificar matrizes de estruturas de covariância que melhor se ajustou aos dados para modelagem do resíduo nessas três características e, em seguida, avaliou-se a respostas de cabras ao calor, com base nesse resultado. Constatou-se cinco matrizes com convergência nas três características. A Simétrica composta heterogênea ajustou-se bem para modelagem do resíduo associado a TR, enquanto a Autorregressiva heterogênea ajustou-se melhor para a FR e FC, de acordo com os critérios de informação de Akaike (AIC), Akaike corrigido (AICc) e o Bayesiano de Schwarz (BIC) utilizados. Com o resíduos de dados dessas três características ajustados, utilizou-se uma análise com modelos mistos para avaliar a Época de coleta (3), Estado fisiológico (3) e Idade do animal (3) foram como efeitos fixos. Constatou-se que a modelagem do resíduo interferiu de modo diferenciado no p valor associado aos efeitos fixos estudados. A época da coleta e interações não influenciaram a variação da TR (P>0,761), que oscilou dentro da faixa padrão para caprinos nos trópicos, mas o Estágio fisiológico da cabra sim (P<0,05). A Temperatura retal e as Frequências cardíaca e respiratória tendem a apresentar estruturas de covariâncias modeláveis com utilização de matrizes de covariâncias residuais especificas, ou seja, a matriz Simétrica composta heterogênea mais adequada para dados da Temperatura retal, enquanto a Autorregressiva heterogênea para as Frequências cardíaca e respiratória, geralmente correlacionas. As cabras da raça avaliadas mantêm a temperatura retal dentro da amplitude de variação apresentada por raças adaptadas a ambiente quente. Isso ocorre independente da condição fisiológica que se encontra, mas com ocorrência de variação na frequência respiratória e cardíaca, não excedendo, no entanto, a faixa normal para caprinos. A gestação condiciona a cabra a elevar a FR na época chuvosa do ano na região para manter a TR na faixa de amplitude normal para caprinos.(AU)

Repeatability estimates in longitudinal data on guava trees

The use of longitudinal measurements is an essential practice both in Psidium guajava L. breeding and in other perennial crops in which covariance structures can be introduced to explain the form of dependence between measurements. Hence, this study aimed to analyze six covariance structures to identify one that best described the correlation between the repeated measurements in time in traits of guava full-sib families. The repeatability coefficient for each trait was estimated and the minimum number of evaluations required for estimates representing the population was determined. The work was performed based on average data of three yield-related variables from nine harvests of a guava tree population evaluated from 2011 to 2018. The best model was chosen based on the Akaike and Schwarz Bayesian information criterion. The autoregressive covariance structure best represented the dependencies among families between crops for all traits. The number of variables of fruits and total yield per plant presented repeatability estimates higher than 0.5 and may be essential traits for indirect selection of others, such as fruit mass, which had an estimated repeatability of 0.24, proving low regularity in the repetition of the character from one cycle to another. It was also possible to define four harvests as the minimum acceptable number of observations necessary on the same individual for these traits; therefore, the repetitions represented the individuals.(AU)

Bayesian joint modeling of longitudinal and spatial survival AIDS data.

Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time-to-event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with non-linear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002-2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states. Copyright © 2016 John Wiley & Sons, Ltd.

Longitudinal data assessment of global stability index in kale leaves

Kale plants are usually sold in natura in street markets and malls. Kale leaves can have their appearance compromised by dehydration and discoloration due to increased post-harvest time exposure. We aimed to analyze the Global Stability Index (GSI) in kale accessions by means of repeated measurement analysis and curve grouping as a complementary form of superior sample identification with regard to post-harvest preservation. Thirty kale accessions were evaluated using a randomized block design with four blocks and five plants per plot. Two commercial leaves per plant were collected, and kept on workbenches in the shade at a temperature of 18 ± 1 °C. Subsequently, the degrees of discoloration and dehydration, total chlorophyll content, and accumulated fresh mass loss were evaluated over a 15-day period. From these data, the GSI was calculated for each day of evaluation. In addition, using mixed models, thirteen co-variance structures were tested. For graphical analysis, thirteen linear and non-linear models were assessed followed by curve grouping using multivariate analysis. The GSI was efficient for differentiating accessions, which became an important tool in post-harvest studies. GSI values were not equally correlated, therefore the use of mixed models became an important approach. The unstructured matrix was the best fit to model the dependence of error. The Melow I model was the best fit for studying the GSI. The accessions UFVJM-10, UFLA-1, COM-1, UFVJM-32, COM-3, UFVJM-8, UFVJM-36 and UFVJM-24, belonging to 3 and 5 clusters, are recommended for crop cultivation and as parental material in breeding programs.

Longitudinal data assessment of global stability index in kale leaves

Kale plants are usually sold in natura in street markets and malls. Kale leaves can have their appearance compromised by dehydration and discoloration due to increased post-harvest time exposure. We aimed to analyze the Global Stability Index (GSI) in kale accessions by means of repeated measurement analysis and curve grouping as a complementary form of superior sample identification with regard to post-harvest preservation. Thirty kale accessions were evaluated using a randomized block design with four blocks and five plants per plot. Two commercial leaves per plant were collected, and kept on workbenches in the shade at a temperature of 18 ± 1 °C. Subsequently, the degrees of discoloration and dehydration, total chlorophyll content, and accumulated fresh mass loss were evaluated over a 15-day period. From these data, the GSI was calculated for each day of evaluation. In addition, using mixed models, thirteen co-variance structures were tested. For graphical analysis, thirteen linear and non-linear models were assessed followed by curve grouping using multivariate analysis. The GSI was efficient for differentiating accessions, which became an important tool in post-harvest studies. GSI values were not equally correlated, therefore the use of mixed models became an important approach. The unstructured matrix was the best fit to model the dependence of error. The Melow I model was the best fit for studying the GSI. The accessions UFVJM-10, UFLA-1, COM-1, UFVJM-32, COM-3, UFVJM-8, UFVJM-36 and UFVJM-24, belonging to 3 and 5 clusters, are recommended for crop cultivation and as parental material in breeding programs.(AU)

Ronda clínica y epidemiológica. Análisis de datos longitudinales / Clinical and epidemiological round. Longitudinal data analysis / Ronda clínica e epidemiológica. Análise de dados longitudinais

El denominado análisis de datos longitudinales (ADL) se refiere a los métodos para evaluar de manera apropiada las medidas de un mismo sujeto que se repiten en el tiempo. El ADL es una herramienta adecuada para entender indicadores de cambio en procesos de salud y enfermedad y para la evaluación del efecto de diversas intervenciones terapéuticas. Se presentan los principales modelos de ADL, sus ventajas y algunos ejemplos recientes de la literatura médica.

Longitudinal data analysis (LDA) refers to the methods designed to evaluate repeated measurements within an individual. LDA is an appropriate tool to address the process of change in health and disease and also to evaluate the efficacy of interventions. We present the main LDA models as well as their advantages and some clinical examples from recent medical literature.

A denominada análise de dados longitudinais (ADL) refere-se aos métodos para avaliar de maneira apropriada as medidas de um mesmo sujeito que se repetem no tempo. O ADL é uma ferramenta adequada para entender indicadores de mudança em processos de saúde e doença e para a avaliação do efeito de diversas intervenções terapêuticas. Apresentam-se os principais modelos de ADL, suas vantagens e alguns exemplos recentes da literatura médica.