Do Non-Response Follow-Ups Improve or Reduce Data Quality?: A Review of the Existing Literature

Olson, Kristen

doi:10.1111/j.1467-985x.2012.01042.x

Cited by 47 publications

(36 citation statements)

References 43 publications

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“…Many researchers have found a relationship to exist between response quality and the time of responding (including Olson, 2013;Kreuter, Müller and Trappmann, 2013). They suggest that the interviewees who respond immediately after being contacted respond better than those who do so following various invitations; something that was also found in our study.…”

Section: Response Qualitysupporting

confidence: 75%

“…Son numerosos los investigadores que han dado cuenta de la relación existente entre la calidad de la respuesta y el momento de responder (entre otros, Olson, 2013;Kreuter, Müller y Trappmann, 2013). Estos plantean que los entrevistados que contestan inmediatamente tras ser contactados responden mejor que aquellos que lo hacen tras diversas invitaciones; hecho que queda probado también en el presente estudio.…”

Section: Calidad De La Respuestaunclassified

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Comparación de métodos de campo en la encuesta

Igúzquiza¹,

Álvarez²

2024

REIS

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ResumenEn este trabajo se presentan los resultados de una investigación a población general que utiliza conjuntamente una encuesta por correo postal, una encuesta telefónica y una encuesta a través de Internet. La muestra objeto de estudio recibe la invitación a cooperar mediante una comunicación por correo, y es el propio seleccionado el que decide cómo responder. La nota analiza la calidad de la respuesta (considerando el número de no respuestas), el tiempo necesario para llevar a cabo el trabajo de campo y el coste de la recogida de información. Los resultados desvelan que la realización de encuestas vía web reducen el tiempo del trabajo de campo, consiguen menor respuesta parcial y presentan un coste ligeramente superior a la encuesta realizada por correo. Ahora bien, la diferente estructura de costes de cada una permite concluir que de haber obtenido el total de los cuestionarios online, la reducción de costes hubiera supuesto un 18,2%. Key words AbstractThis paper presents the results of a mixed-mode survey of the general population using a combination of postal, telephone, and Internet survey protocols. Potential respondents were invited to participate by ordinary mail and were allowed to choose their preferred response mode. The paper focuses on response quality (taking non-responses into consideration), fieldwork time and data collection cost. The results reveal that the Internet survey produces the lowest rate of non-responses and requires significantly less fieldwork time, although it is slightly more costly than the postal survey. However, when differences in cost structure are taken into account, we find that the same number of completed questionnaires could have been obtained through the Internet alone at a cost that is 18.2% lower than the mixed-mode survey. Cómo citarDíaz de Rada, Vidal y Domínguez Álvarez, Juan Antonio (2017). «Comparación de métodos de campo en la encuesta». Revista Española de Investigaciones Sociológicas, Una visión retrospectiva de la evolución en la recogida de información mediante encuesta desvela que el cuestionario con ordenador (CAI) está sustituyendo paulatinamente a la encuesta tradicional presencial. Este cuestionario, además de utilizar todos los tipos de preguntas disponibles (respuesta única, respuesta múltiple, respuesta textual o numérica, etc.), es más sencillo de administrar al llevar a cabo -de forma automática-«saltos» provocados por preguntas filtro, rutas complicadas, etc. No menos importante es que permite establecer reglas de consistencia que son comprobadas antes de grabar la información (Couper y Bosnjak, 2010).El fin de este trabajo es considerar hasta qué punto estas características señaladas por la mayor parte de la literatura son aplicables a una parte de los andaluces residentes en el extranjero. A diferencia de otros trabajos donde es el investigador quien elige el tipo de cuestionario a utilizar, en este el entrevistado decide cómo responderlo, implicando así una preferencia manifiesta hacia uno u otro tipo.Una muestra de la población andaluza ...

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Section: Response Qualitysupporting

confidence: 75%

Section: Calidad De La Respuestaunclassified

Comparación de métodos de campo en la encuesta

Igúzquiza¹,

Álvarez²

2024

REIS

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“…If the answer is "yes", then the analyst has to decide which set of results are more likely to be correct. In making this decision it will be important to carefully consider the details of the response phase, and to consider that using enhanced efforts on converting difficult cases may lead to measurement errors in the responses of difficult cases (Fricker and Tourangeau 2010;Olson 2013). …”

Section: Extra Effort/incentives At the End Of Fieldwork: An Improvemmentioning

confidence: 99%

Do low survey response rates bias results? Evidence from Japan

Rindfuss¹,

Choe²,

Tsuya³

et al. 2015

DemRes

168

114

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BACKGROUNDIn developed countries, response rates have dropped to such low levels that many in the population field question whether the data can provide unbiased results. OBJECTIVEThe paper uses three Japanese surveys conducted in the 2000s to ask whether low survey response rates bias results. A secondary objective is to bring results reported in the survey response literature to the attention of the demographic research community. METHODSUsing a longitudinal survey as well as paradata from a cross-sectional survey, a variety of statistical techniques (chi square, analysis of variance (ANOVA), logistic regression, ordered probit or ordinary least squares regression (OLS), as appropriate) are used to examine response-rate bias. RESULTSEvidence of response-rate bias is found for the univariate distributions of some demographic characteristics, behaviors, and attitudinal items. But when examining relationships between variables in a multivariate analysis, controlling for a variety of background variables, for most dependent variables we do not find evidence of bias from low response rates. COMMENTSThe results have two implications. First, demographers should not presume the presence or absence of low response-rate bias; rather they should test for it in the context of a specific substantive analysis. Second, demographers should lobby data gatherers to collect as much paradata as possible so that rigorous tests for low response-rate bias are possible. IntroductionSample surveys (cross-sectional and longitudinal) have become the dominant data source used by population researchers. Response rates, both the initial response rate and attrition rates in longitudinal studies, have historically been an important rough-andready yardstick to judge data quality. Response rates 6 have been declining in urbanized, high-income countries to the point where many cross-sectional surveys now have response rates below 50% (Atrostic et al. 2001;Brick and Williams 2013;de Leeuw and de Heer 2002;Groves 2011;Singer 2006). The survey literature has long recognized that low response rates only indicate potential bias (e.g., Lessler and Kalsbeck 1992), yet the almost automatic response among most in the population field has been to equate low response rates with poor data quality. Low response rates produce bias only to the extent that there are differences between responders and non-responders on the estimate(s) of interest, and then only if such differences cannot be eliminated or controlled for through the use of observable and available characteristics of responders and non-responders. The difficulty in evaluating non-response bias is that measures of the variable(s) of interest and characteristics of non-responders are generally not observed, and hence the population field has tended to rely on the presumption that low response rates necessarily mean low data quality.In this paper, using surveys designed by demographers and variables that have often been used as dependent variables in demographic research, we examine this 6 ...

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“…Call record data are available for both respondents and non-respondents to nay given survey and are thus prime candidates for the study of nonresponse bias, for example, through level-of-effort analyses, in which early respondents are compared to late responders assuming that later responders are more similar to nonresponders than early responders (Stinchcombe et al 1981;Smith 1984;Schnell, 1998;Kennickell 1999;Chiu et al 2001;Duhart et al 2001;Lynn et al 2002;Lynn 2003;Wang et al 2005;Stoop 2005;Voogt and Saris 2005;; for a meta-analysis of the results, see Olson 2010). With the goal of assessing net quality gains, researchers have used call record data to shed light on the relationship between nonresponse and measurement error (Green 1991;Yan et al 2004;Olson 2006;Peytchev and Peytcheva 2007;Yu and Yan 2007).…”

Section: Examples For Paradata and Their Usementioning

confidence: 99%

Building on Progress: Expanding the Research Infrastructure for the Social, Economic, and Behavioral Sciences

(RAtSWD)¹

2011

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Do Non-Response Follow-Ups Improve or Reduce Data Quality?: A Review of the Existing Literature

Cited by 47 publications

References 43 publications

Comparación de métodos de campo en la encuesta

Comparación de métodos de campo en la encuesta

Do low survey response rates bias results? Evidence from Japan

Building on Progress: Expanding the Research Infrastructure for the Social, Economic, and Behavioral Sciences

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