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    <p>I understand that you want to include in your regression only those groups for which there are exactly 4 observations. If this is the case, then one solution is to count the number of observations per group and condition the regression using <code>if</code>:</p> <pre><code>clear all set more off webuse nlswork xtset idcode list idcode year in 1/50, sepby(idcode) bysort idcode: gen counter = _N xtreg ln_w grade age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure /// c.tenure#c.tenure 2.race not_smsa south if counter == 12, be </code></pre> <p>In this example the regression is conditioned to groups with 12 observations. The <code>xtreg</code> command gives (among other things):</p> <blockquote> <p>Number of obs = 1881</p> <p>Number of groups = 158</p> </blockquote> <p>which you can compare with the result of running the regression without the <code>if</code>:</p> <blockquote> <p>Number of obs = 28091</p> <p>Number of groups = 4697</p> </blockquote> <p>As commented by @NickCox, if you don't mind losing observations you can <code>drop</code> or <code>keep</code> (un)desired groups:</p> <pre><code>bysort idcode: drop if _N != 4 </code></pre> <p>or</p> <pre><code>bysort idcode: keep if _N == 4 </code></pre> <p>followed by an unconditional <code>xtreg</code> (i.e. with no <code>if</code>).</p> <p>Notice that both approaches count missings, so you may need to account for that.</p> <p>On the other hand, you might want to think about why you want to discard that data in your analysis.</p>
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    1. POInclude only complete groups in panel regression using Stata
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    1. USRoberto Ferrer
    1. USRoberto Ferrer
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    1. COA one-liner is to `drop` panels that don't come up to scratch or to `keep` those that do. In the simplest case this would be something like `bysort panelid: keep if _N == 4`. Missing values need extra care and extra code.
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      1. USNick Cox
 

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