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📐 Weighting efficiency

📐 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 :

mceclip1.png

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.

 

 

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