Optimizing Protocols for Random Digit Dial Surveys

Last registered on January 04, 2021

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Pre-Trial

Trial Information

General Information

Title

Optimizing Protocols for Random Digit Dial Surveys

RCT ID

AEARCTR-0006882

Initial registration date

December 29, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

January 04, 2021, 9:10 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Burkina Faso

Region

Country

Colombia

Region

Country

Ghana

Region

Country

Mexico

Region

Country

Philippines

Region

Country

Rwanda

Region

Country

Sierra Leone

Region

Country

Uganda

Region

Country

Zambia

Region

Primary Investigator

Name

Steven Glazerman

Affiliation

Innovations for Poverty Action

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Andrew Dillon

PI Affiliation

Northwestern University

Additional Trial Information

Status

On going

Start date

2020-05-05

End date

2021-09-30

Keywords

Behavior, Other

Additional Keywords

survey implementation

JEL code(s)

C83

Secondary IDs

Abstract

In empirical development economics, it is customary to collect data via face to face household surveys. However, the COVID-19 pandemic and other factors have encouraged a shift to phone surveys for this work, where the research literature on mobile phone surveys in low- and middle-income countries is thin. Much of the literature is also out of date, given the rapid changes in mobile cell phone penetration even among poor households as digital financial tools are used more and more for social protection interventions.

In this study, IPA takes advantage of phone surveys launched in nine countries to embed experiments on the best times and days to initiate phone surveys and the optimal number of attempts for high response rates data quality. We use random digit dial surveys, for which it is automatic to randomly assign cases (initial attempts) to time of day and day of week. By definition, most other variables in call protocols are also randomized because cases (phone numbers to attempt) are dialed in random order.

External Link(s)

Registration Citation

Citation

Dillon, Andrew and Steven Glazerman. 2021. "Optimizing Protocols for Random Digit Dial Surveys." AEA RCT Registry. January 04. https://doi.org/10.1257/rct.6882-1.2

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Vary time of day, day of week, and maximum number of attempts

Time of day is recorded in precise units with timestamp, but for the analysis we group calls into morning (before 12 PM), mid-day (12PM to 3:49PM), and evening (4 PM to 10:59 PM)
For day of week, each day is extracted from timestamp data, but Saturday and Sunday are combined into a single weekend indicator

Intervention Start Date

2020-05-05

Intervention End Date

2021-06-30

Primary Outcomes

Primary Outcomes (end points)

Pickup -- did the respondent answer the phone?
Survey completion - did the respondent complete the interview?
Sample composition (demographic characteristics of respondents)

Primary Outcomes (explanation)

Demographic composition is conditional on having completed the survey.
Age is continuous (years)
Education is collapsed into an indicator for secondary education completed or not.
Gender is self-reported.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Units of analysis are individual cases. A case is a valid phone number (registered SIM card) that could result in a completed phone interview.
Interviewers are assigned cases at random from a list provided by the mobile network operator or a third-party sample provider such as Sample Solutions, who pre-pulse the numbers to verify that they are working, active numbers.
The survey dialer randomly assigns cases over a work week (5, 6, or 7 days) and paradata are recorded for each call attempt. These include time of day, day of week, interviewer ID, and attempt number. We will analyze the first attempt for time-of-day and day-of-week analysis, because all actions taken on subsequent attempts are influenced by call center staff behavior and depend on respondent behavior (e.g. reaching the second attempt requires someone to ignore a call or refuse cooperation on the first attempt).
Analysis is straightforward comparison of pickup and completion rates by day and time.

Experimental Design Details

Randomization Method

Randomization is done with software, by the dialer program within SurveyCTO.

Randomization Unit

Units are "cases", where each case is a pre-pulsed phone number.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

62,663 cases

Sample size: planned number of observations

62,663 cases Conditional analyses will have smaller sample sizes. Analysis of completions conditional on pickup, N = 27,945 Analysis of respondent demographics is based on respondents who completed the survey, N = 7,953

Sample size (or number of clusters) by treatment arms

Time of day: Morning 16,230; Mid-day 27,885; Evening 18,548
Day of week: Range from 8,200 for weekends to 10,970 on Mondays, around 10,000 each weekday

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

IPA IRB

IRB Approval Date

2020-05-05

IRB Approval Number

N/A Board chair approved blanket language to be incorporated into several separate IRB submissions to cover methods experiments that imposed no new burden on respondents

Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?

Yes

Intervention Completion Date

December 15, 2020, 12:00 +00:00

Data Collection Complete

Yes

Data Collection Completion Date

September 30, 2020, 12:00 +00:00

Final Sample Size: Number of Clusters (Unit of Randomization)

64,635 cases attempted (smaller samples for specific analyses)
Cases (first attempt) were randomized to time of day and day of week

Was attrition correlated with treatment status?

Final Sample Size: Total Number of Observations

64,347 -- this was not a clustered design

Final Sample Size (or Number of Clusters) by Treatment Arms

Data Publication

Is public data available?

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Program Files

Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials

Description

Research Methods Brief, part of a series of outputs from this research

Citation

Das, Navishti and Davies, Emma and Dillon, Andrew and Glazerman, Steven and Rosenbaum, Michael, Optimal Timing for Random Digit Dialing (June 2021). Global Poverty Research Lab Working Paper No. 21-107, Available at SSRN: https://ssrn.com/abstract=3875808 or http://dx.doi.org/10.2139/ssrn.3875808

URL

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3875808