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Jennifer Sinibaldi

Datos Biográficos

ID4402108
NOMBREJennifer Sinibaldi
NOMBRESJennifer
APELLIDOSinibaldi
FIRMASINIBALDI J
ORCID0000-0002-4628-5721
VERIFICADOSí
TOTAL DE OBRAS4
TOTAL DE CITAS28
TOTAL COMO AUTOR4
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2013
AÑO MÁS RECIENTE DE PUBLICACIÓN2015
ÍNDICE H3
  • Using Call-Level Interviewer Observations to Improve Response Propensity Models

    Jennifer Sinibaldi, Stephanie Eckman•ARTICLE•Public Opinion Quarterly•2015•Citada por: 2•Referencias: 10

    Response propensities are increasingly being used during data collection for responsive survey design applications. Better propensity models, with more predictive power, are needed to guide responsive interventions during data collection. However, available data on both respondents and nonrespondents to improve these models are limited. This analysis investigates the usefulness of a new type of paradata, in the form of an interviewer observation …

  • Which Is the Better Investment for Nonresponse Adjustment

    Jennifer Sinibaldi, Mark Trappmann et al.•ARTICLE•Public Opinion Quarterly•2014•Citada por: 8•Referencias: 4

    Survey methodologists are searching for covariates to use in nonresponse adjustment models, ultimately hoping to find variables that are highly correlated with both the outcomes of interest and the propensity to respond. These covariates can come from auxiliary data that provide information on both respondents and nonrespondents. Two such types of auxiliary data are interviewer observations (a form of paradata) and commercially available data on …

  • Can Interviewers Effectively Rate the Likelihood of Cases to Cooperate

    Stephanie Eckman, Eckman et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 4•Referencias: 9

    This paper explores how well interviewers can judge which cases are likely to cooperate with a survey request and which are unlikely. Interviewers in a telephone survey rated the response likelihood of each case after every call they placed on a scale from zero to 100, where zero meant that the case would never cooperate and 100 meant that the case certainly would. Analyses of the ratings reveal that they do correlate with the cooperation rate am…

  • Evaluating the Measurement Error of Interviewer Observed Paradata

    Jennifer Sinibaldi, Gabriele B Durrant et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 14•Referencias: 8

    As survey researchers have begun exploiting paradata—for example, for the correction of nonresponse bias—the quality of these data has come into question. Inaccurate information is likely to affect the resulting statistics and conclusions drawn from such data. This paper focuses on one type of paradata, observations made by interviewers during the data-collection process, and assesses the quality of these observations by examining their measureme…

  • Evaluating the Measurement Error of Interviewer Observed Paradata

    Jennifer Sinibaldi, Gabriele B Durrant et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 14•Referencias: 8

    As survey researchers have begun exploiting paradata—for example, for the correction of nonresponse bias—the quality of these data has come into question. Inaccurate information is likely to affect the resulting statistics and conclusions drawn from such data. This paper focuses on one type of paradata, observations made by interviewers during the data-collection process, and assesses the quality of these observations by examining their measureme…

  • Which Is the Better Investment for Nonresponse Adjustment

    Jennifer Sinibaldi, Mark Trappmann et al.•ARTICLE•Public Opinion Quarterly•2014•Citada por: 8•Referencias: 4

    Survey methodologists are searching for covariates to use in nonresponse adjustment models, ultimately hoping to find variables that are highly correlated with both the outcomes of interest and the propensity to respond. These covariates can come from auxiliary data that provide information on both respondents and nonrespondents. Two such types of auxiliary data are interviewer observations (a form of paradata) and commercially available data on …

  • Can Interviewers Effectively Rate the Likelihood of Cases to Cooperate

    Stephanie Eckman, Eckman et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 4•Referencias: 9

    This paper explores how well interviewers can judge which cases are likely to cooperate with a survey request and which are unlikely. Interviewers in a telephone survey rated the response likelihood of each case after every call they placed on a scale from zero to 100, where zero meant that the case would never cooperate and 100 meant that the case certainly would. Analyses of the ratings reveal that they do correlate with the cooperation rate am…

  • Using Call-Level Interviewer Observations to Improve Response Propensity Models

    Jennifer Sinibaldi, Stephanie Eckman•ARTICLE•Public Opinion Quarterly•2015•Citada por: 2•Referencias: 10

    Response propensities are increasingly being used during data collection for responsive survey design applications. Better propensity models, with more predictive power, are needed to guide responsive interventions during data collection. However, available data on both respondents and nonrespondents to improve these models are limited. This analysis investigates the usefulness of a new type of paradata, in the form of an interviewer observation …

  • Can Interviewers Effectively Rate the Likelihood of Cases to Cooperate

    Stephanie Eckman, Eckman et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 4•Referencias: 9

    This paper explores how well interviewers can judge which cases are likely to cooperate with a survey request and which are unlikely. Interviewers in a telephone survey rated the response likelihood of each case after every call they placed on a scale from zero to 100, where zero meant that the case would never cooperate and 100 meant that the case certainly would. Analyses of the ratings reveal that they do correlate with the cooperation rate am…

  • Evaluating the Measurement Error of Interviewer Observed Paradata

    Jennifer Sinibaldi, Gabriele B Durrant et al.•ARTICLE•Public Opinion Quarterly•2013•Citada por: 14•Referencias: 8

    As survey researchers have begun exploiting paradata—for example, for the correction of nonresponse bias—the quality of these data has come into question. Inaccurate information is likely to affect the resulting statistics and conclusions drawn from such data. This paper focuses on one type of paradata, observations made by interviewers during the data-collection process, and assesses the quality of these observations by examining their measureme…

  • Which Is the Better Investment for Nonresponse Adjustment

    Jennifer Sinibaldi, Mark Trappmann et al.•ARTICLE•Public Opinion Quarterly•2014•Citada por: 8•Referencias: 4

    Survey methodologists are searching for covariates to use in nonresponse adjustment models, ultimately hoping to find variables that are highly correlated with both the outcomes of interest and the propensity to respond. These covariates can come from auxiliary data that provide information on both respondents and nonrespondents. Two such types of auxiliary data are interviewer observations (a form of paradata) and commercially available data on …

  • Using Call-Level Interviewer Observations to Improve Response Propensity Models

    Jennifer Sinibaldi, Stephanie Eckman•ARTICLE•Public Opinion Quarterly•2015•Citada por: 2•Referencias: 10

    Response propensities are increasingly being used during data collection for responsive survey design applications. Better propensity models, with more predictive power, are needed to guide responsive interventions during data collection. However, available data on both respondents and nonrespondents to improve these models are limited. This analysis investigates the usefulness of a new type of paradata, in the form of an interviewer observation …

Interview (4 obras) · Mathematics (4 obras) · Psychology (4 obras) · Statistics (4 obras) · Survey Methodology and Nonresponse (4 obras) · Econometrics (3 obras) · Business (2 obras) · Computer Science (2 obras) · Data collection (2 obras) · Economic and Environmental Valuation (2 obras)

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