Número de folhas e de plantas para estimação da média do índice spad em crambe / Number of leaves and plants to estimate the average spad index in crambe

O objetivo deste trabalho foi determinar o número de folhas e de plantas necessário para a estimação da média do índice SPAD em crambe, cultivar 'FMS Brilhante'. Em um experimento foram selecionadas, aleatoriamente, 66 plantas. Nessas plantas, foi mensurado o índice SPAD em seis folhas, escolhidas aleatoriamente em cada planta, aos 34 e 40 dias após a emergência, totalizando 396 folhas em cada avaliação. A partir dos dados do índice SPAD, foram calculadas medidas de tendência central e de variabilidade, verificadas a normalidade e a homogeneidade de variâncias. Foram realizadas análises de variância com base no modelo hierárquico (variação entre plantas e variação entre folhas dentro de plantas). O número de folhas, necessário para a estimação da média do índice SPAD, em cada momento de avaliação (34 e 40 dias após emergência), foi determinado por reamostragens, com reposição. Mensurar uma folha por planta, em 36 plantas (36 folhas), é suficiente para a estimação da média do índice SPAD de crambe, com amplitude do intervalo de confiança de 95% igual a três.

The objective of this work was to determine the number of leaves and plants required to estimate the average SPAD index in crambe, cultivar 'FMS Brilhante'. In one experiment were randomly selected 66 plants. These plants, the SPAD index was measured in six leaves, selected randomly from each plant at 34 and 40 days after emergence, totaling 396 leaves on each evaluation. From data of the SPAD index it was calculated measures of central tendency and variability. Analyses of variance based hierarchical model (variation between plants and variation among leaves into plants) were carried. The number of leaves required to estimate the average SPAD index, at each evaluation point (34 and 40 days after emergence), was determined by resampling with replacement. Measure a leaf per plant on 36 plants (36 leaves), is sufficient to estimate the average SPAD index of crambe, with amplitude of confidence interval of 95% equal to three.

Complex sample design effects and inference for Korea National Health and Nutrition Examination Survey data

Nutritional researchers world-wide are using large-scale sample survey methods to study nutritional health epidemiology and services utilization in general, non-clinical populations. This article provides a review of important statistical methods and software that apply to descriptive and multivariate analysis of data collected in sample surveys, such as national health and nutrition examination survey. A comparative data analysis of the Korea National Health and Nutrition Examination Survey (KNHANES) was used to illustrate analytical procedures and design effects for survey estimates of population statistics, model parameters, and test statistics. This article focused on the following points, method of approach to analyze of the sample survey data, right software tools available to perform these analyses, and correct survey analysis methods important to interpretation of survey data. It addresses the question of approaches to analysis of complex sample survey data. The latest developments in software tools for analysis of complex sample survey data are covered, and empirical examples are presented that illustrate the impact of survey sample design effects on the parameter estimates, test statistics, and significance probabilities (p values) for univariate and multivariate analyses.