0000010026 00000 n 0000014354 00000 n %�쏢 0000016529 00000 n 0000016340 00000 n 3.1PPS Sampling without Replacement using SAS 2.3.1 Estimation of y U and t A natural estimator for the population mean y U is the sample mean y. <> 0000014744 00000 n 0000006275 00000 n 0000015548 00000 n 0000019260 00000 n 0000002069 00000 n 0000007565 00000 n 0000004747 00000 n H�b```f``y������� �� @1v��=Ii��-�@����Dl>0���>1��ΉNɬ֬�/�� 59 0 obj << /Linearized 1 /O 61 /H [ 1261 454 ] /L 97755 /E 38834 /N 6 /T 96457 >> endobj xref 59 42 0000000016 00000 n 0000015766 00000 n 0000007543 00000 n 0000017938 00000 n In the approach of Fearnhead and Cli ord (2003), the authors use what we characterize as a probability proportional to size sam-pling design. 0000019238 00000 n is a probability measure on all the possible samples so that p(s) ≥ 0, for all s∈U, and s∈U p(s) = 1. 0000017123 00000 n 0000013028 00000 n ?O��Ѧ`r��Z�q�� �™w� ���D�C��t�=;-P��?v]qer�T�t�f��j�*���ܑem+¸? Sampling with probability proportional to size is usually done with replacement, for if it is done without replacement, the probability ceases to be strictly proportional to size, unless some special device is used, such as that proposed by Yates and Grundy, which is rather complicated for n = 2 and hardly practicable for n > 2. 0000012673 00000 n %PDF-1.4 0000006297 00000 n 0000026603 00000 n ���x��1��� |�����X��������#��_J��O�����ޖ��kV��;LR�=���Z��� P ��,�!J�� ��QV� ׻˜|��D�.��R�. Probability proportion to size is a sampling procedure under which the probability of a unit being selected is proportional to the size of the ultimate unit, giving larger clusters a greater probability of selection and smaller clusters a lower probability. 0000008867 00000 n 0000001261 00000 n 0000010048 00000 n stream Download full-text PDF Read ... Hansen–Hurwitz estimator based on a probability proportional to size with replacement sample involving the same number of draws. 0000004725 00000 n Introduction 0000026681 00000 n 0000020491 00000 n @��&2C�Hv�9s� �-w�:�g�]�����<1����v ���{y��J�����y+!�sp���? These ideas … 0000017960 00000 n ��Nt#H��lw��uwM�p�"\: 8J�[սγ��JS��mM�!��B�'����ل�Kbd�Nx��z���6�t|ʯ���'8�t���L˸r'k m�����C��H1G��~h��&j��z�98K+�n��Q�0�)A8���6�hw�L���'Ԁ�\��_u�칔���B� 0000008845 00000 n 0000003432 00000 n 0000016051 00000 n 0000011386 00000 n 0000002625 00000 n trailer << /Size 101 /Info 57 0 R /Root 60 0 R /Prev 96447 /ID[<13146a89059fea3a85fbe36bb8243a59><7250ad3534ea46b0da45fd493d87757f>] >> startxref 0 %%EOF 60 0 obj << /Type /Catalog /Pages 56 0 R /Metadata 58 0 R >> endobj 99 0 obj << /S 257 /Filter /FlateDecode /Length 100 0 R >> stream 0000011408 00000 n x��\�sܶ���_�ǻN�'��Nӎ;�6�n&rd}X�H�"�n㿾 H rA�N';�4�I`�X ����n(a����88�]��Gݼ{\��͏��V?���� ��o�W;�C�82��%�j�;���hU#���v�n6��$o�a���]���?�v����"���d���C�7ݐ۶�~x����;�3������2�Rd-'�4���sdO�'��"T3+�ONDk�X_naJ��ϯ7[F�l��eK�ԆS�~��r����.υ3��تV2 ��o$�� �7��/`.N��ѯb�`��7����!��L}�Q������r�2�! A sampling design p(.) 0000016750 00000 n Variance estimation is also discussed. 5 0 obj SAMPLE EXPANSION FOR PROBABILITY PROPORTIONAL TO SIZE WITHOUT REPLACEMENT SAMPLING Lawrence R. Ernst [email protected] Bureau of Labor Statistics, 2 Massachusetts Ave., N.E., Room 3160, Washington, DC 20212-0001 KEY WORDS: PPS sampling, Sample expansion, Tillé’s method, National Compensation Survey 1. 0000001693 00000 n For any SRS of size nfrom a population of size N, we have P(S) = 1= N n: Unless otherwise speci ed, we will assume sampling is without replacement. 0000033586 00000 n Unbiased estimation is obtained using the Hansen–Hurvitz estimator in the case of PPS with replacement sampling and the Horvitz–Thompson estimator in the case of probability proportional to size without replacement (PPSWOR) sampling. 0000003917 00000 n Sample selection under PPS without replacement sampling using statistical software are given in following sections. %PDF-1.2 %���� 0000017866 00000 n pling, but the sampling and resampling steps are replaced by a single without-replacement sampling step.