Journal of Survey Statistics and Methodology

The Journal of Survey Statistics and Methodology publishes cutting-edge scholarly articles on statistical and methodological issues. Also @JSurvStatMeth@science

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

We hope this second special issue inspires continued international collaboration, knowledge sharing & future research.

@AAPOR @AmstatNews

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

JSSAM Special Issue Part 2 is now available.

The second of two special issues highlighting survey research across Asia, Africa, Latin America, the Caribbean & Oceania is now online:
🔗https://t.co/j2mAYD1UVk
All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Also:
- Bayesian benchmarking for rare event prevalence
- Prevalence mapping using household survey data

Together, these articles continue the special issue’s focus on methodological innovation across global contexts.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This study evaluates sample size parameters for vaccination coverage cluster surveys, providing practical methodological guidance based on applications from Pakistan.

All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Sample Size Parameters for Vaccination Coverage Cluster Surveys—Insights from Pakistan”
by Dale A. Rhoda et al.

🔗 https://t.co/h9mpvEIeRe

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This article applies transformed Fay-Herriot models to generate quarterly small area estimates of extreme poverty in Brazil, integrating survey and administrative data for improved policy measurement.

All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Quarterly Small Area Estimates of Extreme Poverty in Brazil Using Transformed Fay-Herriot Models”
by Guilherme Anthony Pinheiro Jacob et al.

🔗 https://t.co/PxxSk3H5mi

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This article introduces an empirical likelihood approach for inference under nonignorable sampling and nonresponse, strengthening tools for addressing missing data in complex survey designs.

All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Statistical Inference Under Nonignorable Sampling and Nonresponse—An Empirical Likelihood Approach”
by Danny Pfeffermann et al.

🔗 https://t.co/9eCMsaknwS

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This study applies small area estimation methods to generate localized estimates of child trafficking prevalence in Sierra Leone, illustrating how statistical modeling can inform targeted policy decisions.

All articles are free to read for a limited time

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Small Area Estimation of Child Trafficking Proportions in Chiefdoms of Sierra Leone and Overall Ranking of the Chiefdoms”
by Gauri S. Datta et al.

🔗https://t.co/86YAuDL8DC

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This article examines how excluding survey satisficers can reduce bias in both probability and nonprobability online panels, offering practical guidance for improving data quality in modern survey research.

All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Reducing the Bias from Probability and Nonprobability Online Panels by Excluding Satisficers”
by Sam Slamowicz et al.

🔗 https://t.co/RnAT7rnjvB

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

This article examines how excluding survey satisfiers can reduce bias in both probability and non-probability online panels, offering practical guidance for improving data quality in modern survey research.

All articles are free to read for a limited time.

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Check out this article from JSSAM Special Issue 13(5):

“Reducing the Bias from Probability and Nonprobability Online Panels by Excluding Satisficers”
by Sam Slamowicz et al.

🔗 https://t.co/RnAT7rnjvB

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

We hope this special issue inspires continued international collaboration and methodological innovation.

Guest Editors: Carolina Franco, Mamadou Diallo, Sunghee Lee, Denise Britz do Nascimento Silva, Sharan Sharma & Jibum Kim.

@AAPOR @AmstatNews

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

JSSAM Special Issue 13(5) is now available.

The first of two special issues showcasing survey research across Asia, Africa, Latin America, the Caribbean, and Oceania is now online:

🔗https://t.co/UjKUPh9yPA

Thread ⬇️

[Journal of Survey Statistics and Methodology @JSurvStatMeth]

Also featured:

• Sample size design for vaccination coverage cluster surveys
• Evaluation of bias in nonprobability panels

Together, these contributions illustrate the breadth of survey methodology’s impact.