<div><br>Kristofer:</div><div> </div><div>When I read about it in the '80s, I, too, noticed the similiarity to chi-squared.</div><div> </div><div>Since we don't disagree about Sainte-Lague being the best, then the best I get to do is quibble about _why_ it's the best. :-)</div>
<div> </div><div>The Sainte-Lague index doesn't seem to me to be the important thing. It's a global measure, and that doesn't have the direct importance to individual states, districts or parties, as compared to an individual measure. ...when we're talking about a measure of deviation of s/q values from what they should ideally be.</div>
<div> </div><div>For that, it seems to me that the important measure is also the simplest and most obvious one, the one that results directly from SL's rounding-off:</div><div> </div><div>Each party, state or district is as close as possible to its correct proportional share.</div>
<div> </div><div>But there is one global measure that I consider to be the most important. The measure of correlation between q and s/q.</div><div> </div><div>You know, as desirable as it is for everyone to be as close as possible to their correct proportional share, _bias_ seems to me to be the really important consideration in apportionment and PR. Size-bias. </div>
<div> </div><div>Sainte-Lague Webster is the unbiased divisor method, and SL/Webster and Largest Remainder are the unbiased methods, if, for any interval between integers N and N+1, </div><div>every point in that interval is equally likely to be where we'd find a party, district or state.</div>
<div> </div><div>But that condition doesn't really obtain. Weighted Webster is more unbiased than Webster.</div><div> </div><div>I'm sure that SL/Webster is quite unbiased enough. And it's simple, and it's well-precedented. I don't propose any other method for apportionment or PR.</div>
<div> </div><div>Well, if splitting strategy were ever a problem, and if changing the 1st SL denominator from 1 to 1.4 or 2 didn't satisfactorily get rid of the problem, then I'd suggest Largest-Remainder as the solution. Raph suggested 2. I've read that Scandinavian countries that use Sainte-Lague use 1.4. I haven't heard of any actual problem with splitting strategy. People sometimes write bad-examples of such strategy, but actually doing the strategy would be difficult and dangerous. And even could be feasible and problematic in ordinary SL, it would be much less so with the Modified SL that uses 2 or 1.4 as the first SL denominator.</div>
<div> </div><div>Ideally, in principle, in ordinary SL, splitting could give some people double their rightful s/q. When the 1st SL denominator is changed from1 to 2, they can only get 4/3 of their rightful s/q by that strategy. ...for the great difficulty and risk involved with that strategy.</div>
<div> </div><div>Evidently, splitting strategy is not a problem for modified SL. I merely mentioned Largest-Remainder as a solution in the event that splitting were a problem in Sainte-Lague, and remained so in Modified Sainte-Lague.</div>
<div> </div><div>Though I prefer SL/Webster, and consider it the best, Largest-Remainder deserves credit for its advantages: Like SL, it's unbiased (under the conditions that I specified), and it "satisfies quota"--if a party's number of Hare quotas is between N and N+1, that party will get either N seats or N+1 seats. </div>
<div> </div><div>In Raph's bad-example, LR was unaffected by the splitting strategy, and gave the same allocation as did SL under sincere voting.</div><div> </div><div>Though I respect and praise LR's advantages, it seems that Sainte-Lague, or at least Modified Sainte-Lague, doesn't really have a splitting problem, and that SL is the best. Sainte-Lague should be the recommended allocation method, for PR as well as for apportionment.</div>
<div> </div><div>Mike Ossipoff</div><div> </div><div> </div><div> </div><div> </div><div> </div><div><br> </div><div class="gmail_quote">On Sat, Jul 7, 2012 at 11:56 AM, Kristofer Munsterhjelm <span dir="ltr"><<a href="mailto:km_elmet@lavabit.com" target="_blank">km_elmet@lavabit.com</a>></span> wrote:<br>
<blockquote style="margin:0px 0px 0px 0.8ex;padding-left:1ex;border-left-color:rgb(204,204,204);border-left-width:1px;border-left-style:solid" class="gmail_quote">The Sainte-Laguë index is a measure of disproportionality that is minimized by Sainte-Laguë / Webster. (Michael Gallagher also recommended it as "the standard measure of disproportionality".)<br>
<br>
The Sainte-Laguë index is smiply the sum of, over all parties (or other distinct groups), (V_p - S_p)^2 / V_p, where V_p is the share of votes for party (or group) p, and S_p is its share of seats. If there were as many seats as voters, then V_p - S_p would be 0 and 0/x is 0 for any x != 0, so in the case of perfect proportionality, this index is 0.<br>
<br>
However, the case of perfect disproportionality shows a problem with this index. If there's a party who gets no votes whatsoever, then V_p is 0 and you get a division by zero. It's easy to, for this case, either say 0/0 = 0 or just exclude zero-vote parties (as adding a party with no seats and no votes shouldn't have an effect), but if that party gets a seat, then the index resolves to infinity. It's pretty unlikely that a party with no votes would get a seat, but if a party with a low vote share would happen to get a seat, that could unbalance the index, so it'd be useful to find something that acts like the Sainte-Laguë index but handles those situations better.<br>
<br>
The expression of SUM over p, (V_p - S_p)^2 / V_p looks a lot like the x^2 of the chi-squared test. If we multiply both V_p and S_p by the number of seats, we get a chi-squared test where the expected value is the number of seats the given party "ought" to have (in the ideal case), and the observed value is the number of seats it actually got -- although then the x^2 value is used directly instead of transformed into a p-value.<br>
<br>
And to my knowledge, the same problem exists in the context of chi-squared tests. There, they use rules of thumbs like "where there is only one degree of freedom, the approximation is not reliable if expected frequencies are below 10".<br>
<br>
One could go in two directions, then. First, that the Sainte-Laguë index is related to a chi-squared test of the probability that the seats were sampled from the distribution of ideal number of seats as given by the voters. Then, other ways of measuring goodness-of-fit might work where the Sainte-Laguë index itself fails. Perhaps an exact multinomial test would work for small assemblies. If one needs to have numbers similar to the Sainte-Laguë index, one could just reverse the final step of the chi-squared test (and go from p-value to x^2 rather than vice versa).<br>
Second, improvements to the chi-squared test could be used to improve the Sainte-Laguë index. Again, as an example, one could construct a "Sainte-Laguë G-index": 2 * SUM (over p) of ln(S_p/V_p), which is to the Sainte-Laguë index what the G-test is to the chi-squared test. Note, though, that this still has the original SLI's division-by-zero problem, and to get the same independence of no-vote parties, one'd have to set ln(0/0) = 0.<br>
<br>
(Usual disclaimer: I Am Not A Statistician.)<br>
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