About leex1514

leex1514 · ‎02-16-2022

Thank you RobPratt. This solution works as well.

leex1514 · ‎02-14-2022

For 3 groups i would like to assign, I hope to see each group's mean of N size and mean of score same (similar if not same): group 1 average N size =50 average score=60, group 2 average N size =50 average score=60,, group 3 average N size =50 average score=60 something like this. I am aware the averages can not be exactly same among groups but similar means within one or two points difference.

leex1514 · ‎02-14-2022

It does not look like either method brings me similar average values in each variable. Is there any method how to assign each observation into 5 groups so that each group has similar average of v1 and v2?

leex1514 · ‎02-10-2022

hello folks, I am trying to assign each observation into 3 groups based on two variables (N size and score) so that each group has similar values in two variables ( e.i. average N size and score per group is similar). I have a small size mock up data shown below ( of course my real data is longer). How should I write a code for group assignment? data1 id N size score A 10 131 B 30 127 C 4 109 D 1 110 E 9 125 F 51 127 G 22 119 H 42 130 I 7 100

leex1514 · ‎08-16-2021

The mean and std for student performances not of each item.

leex1514 · ‎08-13-2021

It is not simulation. I need to use my data to draw a sample because there are item response variables associated with each row(person).

leex1514 · ‎08-12-2021

Thank you but I know the IRT. I just need to have a calibration sample with same with population ability distribution so that when a sample is off on the ability distribution (data 1) how that would impact on item parameter estimation vs when a sample is on the ability distribution( population mean and std).

leex1514 · ‎08-12-2021

Items are different each year. Knowing population ability distribution does not solve estimation of items each year students take. It is item response theory and item calibration/linking.

leex1514 · ‎08-12-2021

I am trying to use this sample to calibrate items (of students of certain ability distribution). The purpose is to compare item parameter estimates of my data1 and of matched sample to the population distribution of ability.

leex1514 · ‎08-11-2021

Hello all, I have known parameter values (mean and std of population distribution) and have a particular year's data (data1) of the population. I am trying to use bootstrap sampling to draw a sample from the data 1 to meet the population parameter values of mean and std. The data 1 has pretty big size about n=60,000. Is it possible? thank you leex1514

leex1514 · ‎05-28-2021

I found my error of var2. It occurred when I applied coefficients a and b. I fixed it and ran the whole analysis but still my var1's mean is way higher than the target mean. Is this problem inheriting in my data, nothing much can be done? Dataset R4_502 /*HAVE1*/ The MEANS Procedure Variable N Mean readingscalescore1 228928 357.0903559 white 228989 0.3714764 Sample from R4_503 /*HAVE2*/ The MEANS Procedure Variable N Mean readingscalescore1 5000 387.1486000 white 5000 0.3714000

leex1514 · ‎05-28-2021

For that reason, I changed weight w to w1 and leave var2 as w. But I will change the var2 name to be something completely different to avoid confusion.

leex1514 · ‎05-28-2021

Here are the outputs (var2=w). Obs W _alloc_ 1 0 62.8524 2 1 37.1476 Obs r r0 r1 1 5000 3143 1857 Obs Replicate W COUNT PERCENT 1 1 0 3143 0.2 2 2 0 3143 0.2 3 3 0 3143 0.2 4 4 0 3143 0.2 5 5 0 3143 0.2 6 6 0 3143 0.2 7 7 0 3143 0.2 8 8 0 3143 0.2 9 9 0 3143 0.2 10 10 0 3143 0.2

leex1514 · ‎05-28-2021

I still have no 1s of var2 in samp. I don't know why proc survey does not pick 0 and 1 in the samp.

leex1514 · ‎05-27-2021

Thank you so much for your code! I have tried it but my final sample's means are not meeting targets (mean of var1 is way too high and mean of var2=0) . I found "samp" does not contain var2=1 (only contain var2=0). Maybe the proc surveyselect step is not working properly? Or my data won't work no matter what I do?

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Re: assign observations into groups based on variables

Re: assign observations into groups based on variables

Re: assign observations into groups based on variables

assign observations into groups based on variables

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Resample so that sample statistics match the parameter values

Re: assign observations into groups based on variables

Re: assign observations into groups based on variables

Re: assign observations into groups based on variables

assign observations into groups based on variables

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Re: parametric bootstrap sampling

Resample so that sample statistics match the parameter values

Re: Sampling to meet reference characteristics

Re: Sampling to meet reference characteristics

Re: Sampling to meet reference characteristics

Re: Sampling to meet reference characteristics

Re: Sampling to meet reference characteristics