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EVAULATION OF THE NSCRG SCHOOL SAMPLE Donsig Jang and Xiaojing Lin Third International Conference on Establishment Surveys Montreal, Canada, June 21, 2007.

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Presentation on theme: "EVAULATION OF THE NSCRG SCHOOL SAMPLE Donsig Jang and Xiaojing Lin Third International Conference on Establishment Surveys Montreal, Canada, June 21, 2007."— Presentation transcript:

1 EVAULATION OF THE NSCRG SCHOOL SAMPLE Donsig Jang and Xiaojing Lin Third International Conference on Establishment Surveys Montreal, Canada, June 21, 2007 Donsig Jang and Xiaojing Lin Third International Conference on Establishment Surveys Montreal, Canada, June 21, 2007

2 Outline Sampling options on repeated establishment surveys Reasons to keep the same sample in establishment surveys Issues in keeping the same sample Example: NSRCG school sample Summary Recommendation for 2008 NSRCG School Sample Sampling options on repeated establishment surveys Reasons to keep the same sample in establishment surveys Issues in keeping the same sample Example: NSRCG school sample Summary Recommendation for 2008 NSRCG School Sample

3 Sampling options on repeated establishment surveys Keep the same sample over time with supplemental samples for births –Efficient change estimates BUT –Response burden –Inefficient cross-sectional estimates An independent sample in each survey round Sample coordination to maximize overlaps between samples –Rotation samples (Sigman and Monsour 1995) –Permanent random number technique (Ohlsson 1995, 2001) –Keyfitz procedure (Keyfitz 1951) Keep the same sample over time with supplemental samples for births –Efficient change estimates BUT –Response burden –Inefficient cross-sectional estimates An independent sample in each survey round Sample coordination to maximize overlaps between samples –Rotation samples (Sigman and Monsour 1995) –Permanent random number technique (Ohlsson 1995, 2001) –Keyfitz procedure (Keyfitz 1951)

4 Reasons to keep the same sample in establishment surveys Difficulty in identifying point of contact Costly efforts in gaining participation Often requires nontrivial process to gather information – previous survey participation would help Difficulty in identifying point of contact Costly efforts in gaining participation Often requires nontrivial process to gather information – previous survey participation would help

5 Issues in keeping the same sample Can they be a representative sample of the current cross-sectional population? –Depending on how dynamic the population is over time coverage issues: births vs. deaths sample efficiency: distributional changes Alternatives –Independent sample from the most up-to-date sample frame –Coordination of samples E.g., Keyfitz procedure to maximize the sample overlap between the current and the previous ones Can they be a representative sample of the current cross-sectional population? –Depending on how dynamic the population is over time coverage issues: births vs. deaths sample efficiency: distributional changes Alternatives –Independent sample from the most up-to-date sample frame –Coordination of samples E.g., Keyfitz procedure to maximize the sample overlap between the current and the previous ones

6 National Survey of Recent College Graduates (NSRCG) Repeated every two or three years Collects education, demographic, and employment information from recent college graduates (bachelors and masters) majoring in science,engineering, and health fields Two stage sample design –1 st stage: select schools and obtain the list of graduates from selected schools –2 nd stage: select graduates from the list provided by schools NSF-sponsored survey Repeated every two or three years Collects education, demographic, and employment information from recent college graduates (bachelors and masters) majoring in science,engineering, and health fields Two stage sample design –1 st stage: select schools and obtain the list of graduates from selected schools –2 nd stage: select graduates from the list provided by schools NSF-sponsored survey

7 NSRCG List collection from schools Identify point of contact (usually institutional coordinator) Gather the list of graduates with key sampling and locating information including: –degree award dates –degree level –field of major –race/ethnicity –gender –date of birth –SSN –student ID –mailing addresses including parents addresses –phone numbers (land line, cell) – s, etc. Identify point of contact (usually institutional coordinator) Gather the list of graduates with key sampling and locating information including: –degree award dates –degree level –field of major –race/ethnicity –gender –date of birth –SSN –student ID –mailing addresses including parents addresses –phone numbers (land line, cell) – s, etc.

8 NSRCG List collection from schools (continued) Need a good understanding on the information requested and file format Time consuming and costly efforts –different schools have different issues A crucial part for the quality of the survey –strive to get almost perfect cooperation rate (99%) –Out of 300 schools, only four final refusals in 2003 only five refusals in 2006 Need a good understanding on the information requested and file format Time consuming and costly efforts –different schools have different issues A crucial part for the quality of the survey –strive to get almost perfect cooperation rate (99%) –Out of 300 schools, only four final refusals in 2003 only five refusals in 2006

9 NSRCG School sample selection For 1995, 1997, 1999, 2001 surveys –275 schools initially selected in 1995 and kept with 5 supplemental samples added over three survey rounds (to account for frame coverage) A new sample of 300 schools selected in 2003: –To reflect rapid changes of S&E populations in 1990s –Health field added to the survey as eligible field of study For 1995, 1997, 1999, 2001 surveys –275 schools initially selected in 1995 and kept with 5 supplemental samples added over three survey rounds (to account for frame coverage) A new sample of 300 schools selected in 2003: –To reflect rapid changes of S&E populations in 1990s –Health field added to the survey as eligible field of study

10 NSRCG School sample selection (continued) Probability proportional size (PPS) with composite size measure Composite size measures calculated to achieve equal weights within each of NSRCG analytic domains constructed by a combination of: –degree year, degree level, field of majors, race/ethnicity, and gender Population dynamics –new schools (birth), closed (death), no S&E graduates (temporarily ineligible), etc Coverage issue –distributions of schools changed (in terms of composite size measures) potential factor affecting the sample efficiency Probability proportional size (PPS) with composite size measure Composite size measures calculated to achieve equal weights within each of NSRCG analytic domains constructed by a combination of: –degree year, degree level, field of majors, race/ethnicity, and gender Population dynamics –new schools (birth), closed (death), no S&E graduates (temporarily ineligible), etc Coverage issue –distributions of schools changed (in terms of composite size measures) potential factor affecting the sample efficiency

11 2003 NSRCG school sample In both 2001 and 2003 NSRCG 170 (57%) Only in 2003 NSRCG 130 (43%) Total300 Excessive efforts (time and resources) to achieve 99% of RR (4 schools refused)

12 Distribution of list submission dates in 2003 NSRCG Days

13 School sample after 2003 NSRCG – 2006 NSRCG Frame evaluation 2003 Frame based on AY2001 IPEDS counts 2006 Frame based on AY2003 and AY2004 IPEDS counts

14 Graduate counts dropped from and added to the population

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16 2006 NSRCG School Sample No significant change of the population –Kept the same school sample without any supplemental sample No significant change of the population –Kept the same school sample without any supplemental sample

17 Distribution of list submission dates in 2006 NSRCG Days

18 2008 NSRCG ? Evaluate the current sampling strategy (keeping the same sample) by doing –frame evaluation –comparisons with other sampling schemes Independent PPS Keyfitz procedure Evaluate the current sampling strategy (keeping the same sample) by doing –frame evaluation –comparisons with other sampling schemes Independent PPS Keyfitz procedure

19 2008 NSRCG Frame evaluation 2003 Frame based on AY2001 IPEDS counts 2008 Frame based on AY2006 IPEDS counts

20 Graduate counts dropped from and added to the population

21 Sample Evaluation Three sample selection methods considered –Keep the 2003 school sample with a supplemental sample of size 4 –Independent PPS with composite size measures based on updated frame information –Keyfitz procedure Three sample selection methods considered –Keep the 2003 school sample with a supplemental sample of size 4 –Independent PPS with composite size measures based on updated frame information –Keyfitz procedure

22 PPS sample selection procedure Define Size Measure: where m d is a sample size of domain d, M d is the population size of domain d M id is the population size of domain d in school i domain d is constructed from a combination of: graduate year, degree level, field of major, race/ethnicity, and gender

23 PPS sample selection procedure School i selected with probability (p i ) proportional to size S i Achieve equal weight within each domain d Distributional changes of the NSRCG graduate populations would cause unequal weight variations within domains Independent PPS with up-to-date frame data is desirable if weight variation is severe School i selected with probability (p i ) proportional to size S i Achieve equal weight within each domain d Distributional changes of the NSRCG graduate populations would cause unequal weight variations within domains Independent PPS with up-to-date frame data is desirable if weight variation is severe

24 Keyfitz procedure Maximize the overlap between two samples The first sample (2003 NSRCG) was selected with PPS The second sample inclusion probability is dependent upon: –updated size measures –the first sample inclusion probability –the actual sample realization in the first sample Maximize the overlap between two samples The first sample (2003 NSRCG) was selected with PPS The second sample inclusion probability is dependent upon: –updated size measures –the first sample inclusion probability –the actual sample realization in the first sample

25 Simulation of sampling procedures Generate 1000 school independent samples for each of the following options –Keep the same school sample with a supplemental sample of size 4 from the newly eligible schools (births) –Independent PPS sampling using MOS calculated from 2008 NSRCG frame –Keyfitz procedure Generate 1000 school independent samples for each of the following options –Keep the same school sample with a supplemental sample of size 4 from the newly eligible schools (births) –Independent PPS sampling using MOS calculated from 2008 NSRCG frame –Keyfitz procedure

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28 Summary Keeping the same sample is a cost effective option Concern about statistical inefficiency due to the nature of dynamic population Frame coverage corrected by supplemental sample Evaluate the NSRCG school sample –Empirical frame evaluation –Samples simulated based on two methods Distribution changes (in terms of composite size measure) would make the final sample inefficient: –Weight variation within planned domains –Over or under estimation of graduates in some domains Keeping the same sample is a cost effective option Concern about statistical inefficiency due to the nature of dynamic population Frame coverage corrected by supplemental sample Evaluate the NSRCG school sample –Empirical frame evaluation –Samples simulated based on two methods Distribution changes (in terms of composite size measure) would make the final sample inefficient: –Weight variation within planned domains –Over or under estimation of graduates in some domains

29 Recommendation Keep the same school sample with supplemental sample of size 4 for 2008 NSRCG


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