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Analysing interviewer call record data by using a multilevel discrete-time event history modelling approach

Analysing interviewer call record data by using a multilevel discrete-time event history modelling approach
Analysing interviewer call record data by using a multilevel discrete-time event history modelling approach
In recent years, survey agencies have started to collect detailed call record data, including information on the timing and outcome of each interviewer call to a household. In interview-based household surveys, such information may be used to inform effective interviewer calling behaviours, which are critical in achieving co-operation and reducing the likelihood of refusal. However, call record data can be complex and it is not always clear how best to model such data. We present a general framework for the analysis of call record data by using multilevel event history modelling. A multilevel multinomial logistic regression approach is proposed in which the different possible outcomes at each call are modelled jointly, accounting for the clustering of calls within households and interviewers. Of particular interest are the influences of time varying characteristics on the outcome of a call. The analysis of interviewer call record data is illustrated by using paradata from several face-to-face household surveys with the aim of modelling non-response.
event history analysis, interviewer call record data, multilevel multinomial logistic regression, paradata, survey co-operation
0964-1998
251-269
Durrant, Gabriele B.
14fcc787-2666-46f2-a097-e4b98a210610
D'Arrigo, Julia
07400226-3e74-4795-bd5d-f1071270b1b6
Steele, Fiona
7adddb2a-7213-4423-9101-9f796c15584e
Durrant, Gabriele B.
14fcc787-2666-46f2-a097-e4b98a210610
D'Arrigo, Julia
07400226-3e74-4795-bd5d-f1071270b1b6
Steele, Fiona
7adddb2a-7213-4423-9101-9f796c15584e

Durrant, Gabriele B., D'Arrigo, Julia and Steele, Fiona (2013) Analysing interviewer call record data by using a multilevel discrete-time event history modelling approach. Journal of the Royal Statistical Society: Series A (Statistics in Society), 176 (1), 251-269.

Record type: Article

Abstract

In recent years, survey agencies have started to collect detailed call record data, including information on the timing and outcome of each interviewer call to a household. In interview-based household surveys, such information may be used to inform effective interviewer calling behaviours, which are critical in achieving co-operation and reducing the likelihood of refusal. However, call record data can be complex and it is not always clear how best to model such data. We present a general framework for the analysis of call record data by using multilevel event history modelling. A multilevel multinomial logistic regression approach is proposed in which the different possible outcomes at each call are modelled jointly, accounting for the clustering of calls within households and interviewers. Of particular interest are the influences of time varying characteristics on the outcome of a call. The analysis of interviewer call record data is illustrated by using paradata from several face-to-face household surveys with the aim of modelling non-response.

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More information

e-pub ahead of print date: 20 December 2012
Published date: January 2013
Keywords: event history analysis, interviewer call record data, multilevel multinomial logistic regression, paradata, survey co-operation
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 361618
URI: https://eprints.soton.ac.uk/id/eprint/361618
ISSN: 0964-1998
PURE UUID: f332181a-deb5-46c5-afff-9df954029af1

Catalogue record

Date deposited: 29 Jan 2014 13:17
Last modified: 16 Jul 2019 21:13

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Contributors

Author: Julia D'Arrigo
Author: Fiona Steele

University divisions

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