analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

This file describes the replication material for: Trajectories of mental health problems in childhood and adult voting behaviour: Evidence from the 1970s British Cohort Study. Authors: Lisa-Christine Girard & Martin Okolikj. Accepted in Political Behavior. This dataverse holds the following 4 replication files: 1. data_cleaning_traj.R - This file is designed to load, merge and clean the datasets for the estimation of trajectories along with the rescaling of the age 10 Rutter scale. This file was prepared using R-4.1.1 version. 2. traj_estimation.do - With the dataset merged from data_cleaning_traj.R, we run this file in STATA to create and estimate trajectories, to be included in the full dataset. This file was prepared using STATA 17.0 version. 3. data_cleaning.R - This is the file designed to load, merge and clean all datasets in one for preparation of the main analysis following the trajectory estimation. This file was prepared using R-4.1.1 version. 4. POBE Analysis.do - The analysis file is designed to generate the results from the tables in the published paper along with all supplementary materials. This file was prepared using STATA 17.0 version. The data can be accessed at the following address. It requires user registration under special licence conditions: http://discover.ukdataservice.ac.uk/series/?sn=200001. If you have any questions or spot any errors please contact g.lisachristine@gmail.com or martin.okolic@gmail.com.

This data depository contains all experimental materials, data, and code for Spamann, Lawyers' Role-Induced Bias ... All experimental materials (i.e., exercise and survey instrument) are in the pdf file Spamann_experimentalmaterials_all.pdf. The dataset Newman.dta (Stata 14.2) contains the data collected. The Stata do-file Spamann_role_bias_code.do generates the three figures and other reported statistical information reported in the version of the paper originally posted to SSRN in May 2019. Spamann_role_bias_code_revised.do generates the four figures and other reported statistical information reported in the revision submitted to JLS in March 2020 and ultimately accepted by the journal. Both do-files use Newman.dta. Newman.dta is the result of merging 6 csv files generated by Qualtrics in each of the six semesters from students' survey responses. These 6 csv files, and the do-file rawdata_merge_clean.do to merge them, are also included.

The Panel Study of Income Dynamics–Social, Health, and Economic Longitudinal File (PSID-SHELF) provides an easy-to-use and harmonized longitudinal file for the Panel Study of Income Dynamics (PSID), the longest-running nationally representative household panel survey in the world.The first major benefit of PSID-SHELF is that it provides users with a longitudinal data file that features the complete sample of the PSID's multigenerational panel. The current version of PSID-SHELF includes 42 waves of survey data, ranging from 1968 to 2021. Every individual who has ever been observed in the PSID Main Study is included in PSID-SHELF. There are over 8,000 sample families, comprising more than 900,000 observations from roughly 53,000 sample members (and an additional 30,000 nonsample individuals who have ever lived in a PSID family unit). The second major benefit of PSID-SHELF is that it features a novel set of harmonized measures on a wide range of substantive topics, including: (1) social characteristics (e.g., demographics, family type, education, race and ethnicity); (2) health characteristics (e.g., chronic conditions, COVID-19, dementia, disability); (3) economic characteristics (e.g., earnings, family income, occupations, wealth)—as well as a list of the PSID's essential administrative variables (e.g., survey identifiers, panel status, sample weights, household relationship records). Consequently, PSID-SHELF covers some of the most central variables in the PSID that have been collected for up to five decades.PSID-SHELF can be used as a standalone data file, or it can easily be merged with other PSID data products to add additional public-use variables, by linking variables to a participant’s individual and family unit identifiers. The harmonized longitudinal file accentuates the PSID's strengths through its household panel structure that follows the same families over multiple decades and its multigenerational genealogical design that follows the descendants of PSID families that were originally sampled in 1968, with immigrant refresher samples in 1997–1999 and 2017–2019.Although the PSID strives to ensure longitudinally consistent measurement, there are a number of variables that have changed across waves (e.g., because of new code frames, top-codes, question splitting, or other changes to the survey interview). But data harmonization, by necessity, involves analytic decisions that users may or may not agree with. These decisions are described at a high level in the PSID-SHELF User Guide and Codebook, but only a close review of the construction files that were used to generate PSID-SHELF can fully reveal each analytic decision. The Stata code underlying PSID-SHELF is publicly available not only to allow for such review but also to encourage users, as they become more comfortable with PSID, to use and alter the full code or selected code snippets for their own analytic purposes.Despite multiple code reviews, it is possible that the files used to produce PSID-SHELF contain errors. As such, we encourage users to review the code carefully. If identified, please report any mistakes or errors to us (psidshelf.help@umich.edu). The authors wish to underscore that PSID-SHELF is currently being shared as a data product, in beta, and users are responsible for any errors arising from the provided code and files. Current Version 2025-01 (data release number).Permanent DOIDOI:10.3886/E194322 (data).DOI:10.7302/25205 (documentation).Recommended CitationsPlease cite PSID-SHELF in any product that makes use of the data or documentation. Anyone who uses PSID-SHELF should cite the data or the PSID-SHELF User Guide and Codebook—and, as required by the PSID user agreement, the PSID Main Study.PSID-SHELF data:Pfeffer, Fabian T., Davis Daumler, and Esther Friedman. PSID-SHELF, 1968–2021: The PSID’s Social, Health, and Economic Longitudinal File (PSID-SHELF), Beta Release. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor],