Recent Advances in Estimation Methods for Survey Data

Robyn Ferg Chair
Westat
 
Monday, Aug 5: 2:00 PM - 3:50 PM
5075 
Contributed Papers 
Oregon Convention Center 
Room: CC-C121 

Main Sponsor

Survey Research Methods Section

Presentations

Evaluation of a Modified Gross Flows Estimator for The Current Population Survey

We present a gross flows estimation approach which builds off the paper of Stasny and Fienberg (1985). Our method uses population weighted estimates from two consecutive months of matched data from the Current Population Survey (CPS) using the sampling weights from each of the two matched months to produce two sets of partial gross flows tables. We then use a modeling approach from Stasny and Fienberg to reconcile the two partial tables to produce an estimate of the population gross flows table. Closed form solutions are presented which require an optimization solution to determine Lagrange parameters. We use the method to produce estimated gross flows tables for CPS from 2003-2023 and estimate the variance of the estimates by replication. 

Keywords

Monthly Labor Force Transitions

Survey Weights 

View Abstract 2365

Co-Author

Connor Doherty

First Author

Stephen Miller, Bureau of Labor Statistics

Presenting Author

Connor Doherty

Exploratory Analysis that redefined the parameter of a variable in Consumer Price Index Housing Age

Rent and owner's equivalent rent in Consumer Price Index (CPI) uses building's age bias and structural change factors. These factors are calculated each December, then run in January, and put into production use for the following 12 months. A multivariable regression model with 35 independent variables and one dependent (unit's rent) variable is used to calculate these factors. One of the independent variables is the product of the building's age (the current year minus the year a structure is built) and a binary variable, "old". The "old" binary variable is defined as if the unit is built in 1919 or earlier, or if the unit is built in 1920 or later. This "old" parameter is defined in a static manner that underperforms in statistical significance and restricts CPI methodology. An alternative, less restrictive, definition of the "old" parameter which performs with higher statistical significance is found in this research. 

Keywords

CPI

building's age bias

exploratory analysis

python 

View Abstract 3684

Co-Author(s)

Ayme Tomson, BLS
Benjamin Houck, BLS
Chun Wing Tse, BLS

First Author

Alice Yu

Presenting Author

Alice Yu

Fitting multilevel models using STEPS data from multiple countries for estimating health outcomes

With an increased interest in global health outcomes for policy makers looking to understand their own country's health or those interested in global health, there has been increased speculation on whether the use of aggregated data is adequate for accurate predictions on the country level. An alternative to this is to use individual level survey health data from each country. The current main reason for taking this route is so health outcome predictions are made using complex survey design information which would otherwise be unusable through aggregation.

Our analysis uses a multilevel model with random intercepts for each country and models diabetes prevalence as a function of individual level predictors such as body mass index (BMI), age, gender, and highest completed education level. We also include a country's gross domestic output (GDP) class as a country level predictor. These predictions are then adjusted using complex survey design features to specify inferences of estimated diabetes prevalence to each country's population. 

Keywords

multilevel logit model

diabetes

chronic disease

public health

disease reporting 

View Abstract 2539

Co-Author

Yajuan Si, University of Michigan

First Author

Timothy Raxworthy

Presenting Author

Timothy Raxworthy

Future of Tuned Ratio Unbiased Mean Predictor (TRUMP) with the Unified Scrambling Approach (USA)

The Tuned Ratio Unbiased Mean Predictor (TRUMP) was introduced by Singh and Sedory (2017: Survey Research Methods Section, Proceedings of the American Statistical Association, pp. 1746-1759). They have shown that the proposed TRUMP when utilizing First Basic Information (FBI) about the TRUMP care coefficient, can perform better than the Best Linear Unbiased Estimator (BLUE) and also can perform better than the Best Linear Unbiased Predictor (BLUP). Warner (1965: Journal of the American Statistical Association, pp. 63-69) introduced the idea of estimating the population proportion of a sensitive attribute by making use of randomization device. Later on, the idea was extended to estimate the population mean of a sensitive variable by making use of an approach involving additive and multiplicative scrambling variables. In this paper, we will study the future of the TRUMP with a Unified Scrambling Approach (USA) along the lines of Singh, Joarder and King (1996: Australian Journal of Statistics, pp. 201-211). Making a great adjustment (MAGA) by means of scrambling variables may help TRUMP have more precise estimates of frauds, induced abortions, illegal immigration, extramarital relations, tax returns, illegal drugs, and cheating etc. The results based on theory and simulation study will be reported. 

Keywords

Population Mean

Scrambled Responses

Jackknifing

TRUMP cuts

Linear model 

View Abstract 2488

Co-Author

Stephen Sedory, Texas A & M University - Kingsville

First Author

Sarjinder Singh, Texas A&M University-Kingsville

Presenting Author

Sarjinder Singh, Texas A&M University-Kingsville

Implementing weighted interval censoring survival analysis on tobacco regulatory science

Nicotine inhaled after 1-hour hookah session is higher than nicotine in a pack of cigarettes. The Population Assessment of Tobacco and Health (PATH) Study is a national longitudinal study of tobacco use and how it affects the health of people in the United States (2013-2021). PATH implemented a complex design that requires base and 100 balance repeated replicate weights to obtain variance estimates. Weighted interval-censoring survival analysis was used to estimate effect of hookah use on the age of asthma onset using the first wave of PATH participation sampling weights with a Fay correction factor of 0.3. Lower and upper age bounds were estimated. The effect of hookah use on the age of asthma onset was estimated using weighted interval-censoring-Cox regression with cubic splines (3 knots) as the baseline hazard function. Adults (≥18 years old) who reported an average length of hookah session of more than 30 minutes had a 352% increase risk in the onset of asthma at earlier ages in comparison to never or <30 minutes hookah users (HR: 4.52, 95%CI: 1.61-12.67). Attendees will learn how to implement interval-censoring survival analysis with balance repeated replicate weights. 

Keywords

Interval Censoring Hazard Function

Balanced Repeated Replicate Weights

Sampling weights

Fay's variance estimation 

View Abstract 3010

Co-Author(s)

Sarah Valencia, Michael & Susan Dell Center for Healthy Living. University of Texas Health Science Center Houston
Pushan P Jani, The University of Texas Health Science Center at Houston, School of Medicine
Melissa B Harrell, The University of Texas Health Science Center at Houston, School of Public Health

First Author

Adriana Perez, University of Texas At Houston, Health Science Center

Presenting Author

Adriana Perez, University of Texas At Houston, Health Science Center

Non-commercial catch estimation of pelagic species in the main Hawaiian Islands

The Hawaii Marine Recreational Fishing Survey (HMRFS) provides non-commercial catch estimates for mahimahi, skipjack tuna, yellowfin tuna, wahoo, blue marlin, and striped marlin in the main Hawaiian Islands. Stock assessments have sought to use HMRFS estimates as strictly non-commercial complements to the mandatory commercial reporting system. HMRFS is known to encounter fishers that sometimes sell their catch. In order to avoid double counting sold catch between the two data sets and provide a wholly non-commercial HMRFS catch estimate (product of catch rate and fishing effort), catch claimed as unsold was used for catch rate estimation following the approach used for the recent main Hawaiian Islands Deep7 bottomfish stock assessment. Annual and grand mean weights were used to convert estimated catch numbers to catch weights, based on the number of weight measurements available for each species. We have collaborated with a working group of the Western Pacific Regional Fishery Management Council to provide non-commercial catch estimates of the six pelagic species for the Stock Assessment and Fishery Evaluation report of the Council's Pelagic Plan Team. 

Keywords

Hawaii Marine Recreational Fishing Survey (HMRFS)

pelagic species

non-commercial catch

fishing effort

catch rate

stock assessment and fishery evaluation (SAFE) 

View Abstract 3519

Co-Author

Toby Matthews, PIFSC, NOAA Fisheries

First Author

Hongguang Ma, PIFSC, NOAA Fisheries

Presenting Author

Hongguang Ma, PIFSC, NOAA Fisheries

Some Results from the Continuous Count Study

The Continuous Count Study is researching how information and lower-level geographic and demographic characteristic estimates can be generated throughout the decade to help inform the data collection and estimation strategy for the 2030 Census. At the conception, this study has two parts. The first is an annual administrative record population estimates program building on the use of administrative records in the 2020 Census and the Real Time Administrative Record Census evaluation. The second part is researching population estimation and small area estimation techniques to generate alternative population estimates that can be used to assess the quality of the administrative record data results. This paper summarizes some initial results from the Continuous Count Study, focusing on the initial estimates for lower geographic and demographic domains. 

Keywords

administrative records

population estimates

small area estimation 

View Abstract 2218

Co-Author

Vincent T. Mule, U.S. Census Bureau

First Author

Mary Mulry, US Government

Presenting Author

Mary Mulry, US Government