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POBetween/within standard deviations in R
 

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  1. POBetween/within standard deviations in R
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    <p>When working on a hierarchical/multilevel/panel dataset, it may be very useful to adopt a package which returns the within- and between-group standard deviations of the available variables. </p> <p>This is something that with the following data in <code>Stata</code> can be easily done through the command</p> <pre><code>xtsum, i(momid) </code></pre> <p>I made a research, but I cannot find any <code>R</code> package which can do that.. </p> <p><strong>edit:</strong></p> <p>Just to fix ideas, an example of hierarchical dataset could be this:</p> <pre><code>son_id mom_id hispanic mom_smoke son_birthweigth 1 1 1 1 3950 2 1 1 0 3890 3 1 1 0 3990 1 2 0 1 4200 2 2 0 1 4120 1 3 0 0 2975 2 3 0 1 2980 </code></pre> <p>The "multilevel" structure is given by the fact that each mother (higher level) has two or more sons (lower level). Hence, each mother defines a group of observations.</p> <p>Accordingly, each dataset variable can vary either between and within mothers or only between mothers. <code>birtweigth</code> varies among mothers, but also within the same mother. Instead, <code>hispanic</code> is fixed for the same mother.</p> <p>For example, the within-mother variance of <code>son_birthweigth</code> is:</p> <pre><code># mom1 means bwt_mean1 &lt;- (3950+3890+3990)/3 bwt_mean2 &lt;- (4200+4120)/2 bwt_mean3 &lt;- (2975+2980)/2 # Within-mother variance for birthweigth ((3950-bwt_mean1)^2 + (3890-bwt_mean1)^2 + (3990-bwt_mean1)^2 + (4200-bwt_mean2)^2 + (4120-bwt_mean2)^2 + (2975-bwt_mean3)^2 + (2980-bwt_mean3)^2)/(7-1) </code></pre> <p>While the between-mother variance is:</p> <pre><code># overall mean of birthweigth: # mean &lt;- sum(data$son_birthweigth)/length(data$son_birthweigth) mean &lt;- (3950+3890+3990+4200+4120+2975+2980)/7 # within variance: ((bwt_mean1-mean)^2 + (bwt_mean2-mean)^2 + (bwt_mean3-mean)^2)/(3-1) </code></pre>
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    1. COdo you mean raw moments or estimates from a hierarchical model? If the latter, does `VarCorr` do what you want (from `nlme::lme` or `lme4::lmer`)?
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    2. COI mean the sample moments of the empirical distributions of variables, where each variable's overall standard deviation can be split into the within- and between-cluster components.
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    3. CO@Stezzo yes you give the data. It would better to give also the expected result. It is not clear, do you want to compute the moments of `son_birthweigth` over other categorical variables?
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