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# 统计作业代写Statistics代考|The Basics of Multilevel Regression Models

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• Date Analysis数据分析
• Actuarial Science 精算科学
• Bayesian Statistics 贝叶斯统计
• Generalized Linear Model 广义线性模型
• Macroeconomic statistics 宏观统计学
• Microeconomic statistics 微观统计学
• Logistic regression 逻辑回归
• linear regression 线性回归

## 统计作业代写Statistics代考|these relationships

Multilevel models-also known as hierarchical models and mixed-effects models-stem from developments in agricultural statistics, educational statistics, biometry, and econometrics. Long ago, agricultural researchers studying crop growth developed methods for analyzing plants in multiple shared environments or plots of land. Yet if one wished to extrapolate findings to the broader “population” of plants, one needed to be able to consider that the relationships found in an analysis might be “random.” Models that view these relationships as different, or random, rather than fixed across environments or plots, are called random-effects models. Not only do the characteristics of a plant vary (since there are many plants to examine), but the relationships between these characteristics (e.g., how much water the plant receives) and some outcome of interest (e.g., plant growth) vary across environments or plots of land. ${ }^{1}$

## 统计作业代写STATISTICS代考|raised

We are initially interested in the two variance measures in the randomeffects panel because they give some indication of whether more variability in income occurs between towns or between individuals. In this model, the variance between individuals $\left(\sigma_{e}^{2}=4.28\right)$ is substantially larger than the variance between towns $\left(\sigma_{u}^{2}=0.17\right)$, which is often the case in community studies since variability in attitudes, behaviors, and so forth is typically larger across individuals than across groups. One way to characterize the relative degree of variability is with a ratio measure of the group-level variance to the total variance. For LRM15.1, the computation is provided in Equation 15.2.
$$\operatorname{ICC}(\rho)=\frac{\sigma_{u}^{2}}{\sigma_{u}^{2}+\sigma_{\varepsilon}^{2}}=\frac{0.17}{0.17+4.28}=0.038$$
Called the intraclass correlation, or ICC, ${ }^{4}$ it measures the proportion of variability in the outcome that is between groups. Thus, about $3.8 \%$ of the variability in income is between towns; most of the variability occurs within towns (or between individuals). The ICC is also called the cluster effect.

## matlab代写

MATLAB是一个编程和数值计算平台，被数百万工程师和科学家用来分析数据、开发算法和创建模型。

MATLAB is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models.