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Jessica P Kunke

Dados Biográficos

ID4168554
NOMEJessica P Kunke
PRENOMESJessica P
SOBRENOMEKunke
ASSINATURAKUNKE J P
AFILIAÇÕESStatistics and Sociology, University of Washington, Seattle, WA, USA
ORCID0009-0006-1475-3734
VERIFICADOSim
TOTAL DE OBRAS2
TOTAL DE CITAÇÕES3
OBRAS COMO AUTOR2
OBRAS COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2024
ANO MAIS RECENTE DE PUBLICAÇÃO2025
ÍNDICE H1
  • Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method

    Open Access•Ian Laga, Jessica P Kunke et al.•ARTICLE•Sociological Methods & Research•2025•Referências: 13

    The Network Scale-up Method (NSUM) uses social networks and answers to 'How many X's do you know?' questions to estimate sizes of groups excluded by standard surveys. This paper addresses the bias caused by varying average social network sizes across populations, commonly referred to as the degree ratio bias. This bias likely exists for all populations, resulting in either positively or negatively biased population size estimates. We show how the…

  • Comparing the Robustness of Simple Network Scale-Up Method Estimators

    Open Access•Jessica P Kunke, Ian Laga et al.•ARTICLE•Sociological Methodology•2024•Citada por: 3•Referências: 7

    The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps invo…

  • Comparing the Robustness of Simple Network Scale-Up Method Estimators

    Open Access•Jessica P Kunke, Ian Laga et al.•ARTICLE•Sociological Methodology•2024•Citada por: 3•Referências: 7

    The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps invo…

  • Comparing the Robustness of Simple Network Scale-Up Method Estimators

    Open Access•Jessica P Kunke, Ian Laga et al.•ARTICLE•Sociological Methodology•2024•Citada por: 3•Referências: 7

    The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps invo…

  • Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method

    Open Access•Ian Laga, Jessica P Kunke et al.•ARTICLE•Sociological Methods & Research•2025•Referências: 13

    The Network Scale-up Method (NSUM) uses social networks and answers to 'How many X's do you know?' questions to estimate sizes of groups excluded by standard surveys. This paper addresses the bias caused by varying average social network sizes across populations, commonly referred to as the degree ratio bias. This bias likely exists for all populations, resulting in either positively or negatively biased population size estimates. We show how the…

Computer Science (2 obras) · Econometrics (2 obras) · Mathematics (2 obras) · Statistics (2 obras) · Advanced Causal Inference Techniques (1 obra) · Complex Network Analysis Techniques (1 obra) · Degree (music) (1 obra) · Demography (1 obra) · Demography (1 obra) · Economics (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae