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Optimizing Protocols for Random Digit Dial Surveys

Last registered on January 04, 2021


Trial Information

General Information

Optimizing Protocols for Random Digit Dial Surveys
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.



Primary Investigator

Innovations for Poverty Action

Other Primary Investigator(s)

PI Affiliation
Northwestern University

Additional Trial Information

On going
Start date
End date
Secondary IDs
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 Much of the literature is also out of date, given the rapid changes in mobile cell phone penetration even among poor households as digital financial tools are used more and more for social protection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

Dillon, Andrew and Steven Glazerman. 2021. "Optimizing Protocols for Random Digit Dial Surveys." AEA RCT Registry. January 04.
Experimental Details


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
Intervention End Date

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

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)

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
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


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
December 15, 2020, 12:00 +00:00
Data Collection Complete
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
bk_dayofwee | k | Freq. Percent Cum. ------------+----------------------------------- Monday | 11,244 17.47 17.47 Tuesday | 10,893 16.93 34.40 Wednesday | 10,886 16.92 51.32 Thursday | 11,042 17.16 68.48 Friday | 11,747 18.26 86.74 Weekend | 8,535 13.26 100.00 ------------+----------------------------------- Total | 64,347 100.00 bk_timeofday | Freq. Percent Cum. ---------------+----------------------------------- Morning (7-11) | 17,076 26.55 26.55 Midday (12-3) | 28,718 44.65 71.19 Evening (4-10) | 18,529 28.81 100.00 ---------------+----------------------------------- Total | 64,323 100.00
Data Publication

Data Publication

Is public data available?

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Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials

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