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# 📐 Weighting efficiency

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The  weighting efficiency  provides the amount of distortion that was needed to arrive at the weighted figures. I.E how much the data is manipulated by the weighting.

The result is stored  in the report of weighting located into the  survey.dat directory

A low efficiency indicates a larger bias introduced by the weights.

You'll find it into the weighting's report and below the formula to calculate it :

For eg.

 w i w i² i1 0.820508273 0.67323383 i2 1.027660121 1.05608532 i3 0.798126889 0.63700653 i4 1.813092082 3.2873029 i5 0.524670726 0.27527937 i6 1.682138128 2.82958868 i7 0.066485204 0.00442028 i8 1.524746555 2.32485206 i9 0.571220139 0.32629245 i10 1.878748796 3.52969704 i11 0.070238083 0.00493339 i12 1.840453697 3.38726981 i13 0.683791839 0.46757128 i14 1.00838961 1.01684961 i15 0.833383964 0.69452883 i16 1.330310173 1.76972516 i17 0.602917671 0.36350972 i18 1.257201562 1.58055577 i19 0.632265608 0.3997598 i20 1.451447184 2.10669893 i21 0.622107103 0.38701725 i22 1.252551275 1.5688847 i23 0.966905785 0.9349068 i24 1.561603913 2.43860678 Sum 24.82096438 32.0645763 sum(wi) sum(wi²)

 n 24 sum(wi) 24.82096438 sum(wi)² 616.0802728 sum(wi²) 32.06457627 WE = 616.080273 / (24 * 32.0645763) WE 80.06 % The weighting reduces the reliability of the  sample of  19.1% (~100 - 80.06 ~) In other words , it's like we removed 5 persons from our sample (24 X 80.06 % =19)

Our sample is matching  to 80.06% of the population and the effective base is equal to 19

When the weighting efficiency is below to 80% , means that you have some mismatch between the sample and the population.

And when is below to 70% , we recommend you to check the weight design.