The latest estimates from IHP’s SLOTS MRP model (revised 01/2024) show modest increases in support for NPP/JVP and SJB, with weakening support for the UNP and “Other” parties, continuing trends since July 2023. NPP/JVP lead with 44% (+2) support of Sri Lankan adult voters, followed by SJB with 30% (+1), the SLPP at 9% (+1), the UNP at 4% (-1), and ITAK at 4% (unchanged). The February estimates are provisional and are associated with a margin of error of 1–3% for the four leading parties. Compared to IHP’s February release, IHP estimates of NPP/JVP and SJB support in Jan. 2024 were revised +2 and -1 points.

These estimates are for all adults and not for likely voters, and are based on the 01/ 2024 revision of the IHP SLOTS Multilevel Regression and Poststratification (MRP) model. IHP is working on improving its likely voter model and will resume release of voting intent in likely voters in a future update. But it should be noted that differences in voting intent shares between all adults and likely voters have typically been 1–2% for most estimates in the past two years.

This February 2024 update is based on 16,248 interviews conducted with adults across Sri Lanka since Oct. 2021, including 575 interviews carried out in Feb. 2024. IHP’s SLOTS MRP methodology first estimates the relationship between a wide variety of characteristics about respondents and their opinions – in this case, ‘If there was a General Election today, which party would you vote for?’– in a multilevel statistical model. It then uses a large data file that is calibrated to the national population to predict voting intent in each month since Oct. 2021, according to what the multilevel model says about their probability of voting for various parties (‘post-stratification’) at each point in time. The multilevel model was estimated 100 times to reflect underlying uncertainties in the model and to obtain margins of error.

About IHP

IHP is an independent, non-partisan research centre based in Colombo, Sri Lanka. The SLOTS lead investigator is Dr Ravi Rannan-Eliya of IHP, who has trained in public opinion polling at Harvard University and has conducted numerous surveys over three decades. 

Methodology details

SLOTS combines interviews from a national sample of adults (ages 18 and over) reached by random digit dialling of mobile numbers, and others coming from a national panel of respondents who were previously recruited through random selection and face-to-face interviews. IHP estimates voting intent using an adaptation of Multilevel Regression and Post-Stratification (MRP), with multiple imputations to account for uncertainties in its modelling, exploiting data from all SLOTS interviews to estimate voting in a particular month. 

The February 2024 MRP estimates are based on 16,248 interviews conducted from 1 October 2021–24 March 2024, including 575 interviews conducted in February 2024. The margin of error is assessed as 0.9–1.4% for the UNP, SLPP, SLFP, ITAK, SLMC, CWC, and 1.6–2.9% for NPP/JVP, SJB and the “other” parties. A total of 100 bootstraps were used to estimate margins of error.

MRP is a method that is increasingly used by polling firms in other countries to leverage small samples, most notably by YouGov which used it to forecast results of the UK Brexit Referendum and recent UK general elections. All estimates are adjusted to ensure the sample matches the national population with respect to age, sex, ethnicity, socioeconomic status, education, geographical location, and voting in the 2019 Presidential and 2020 General Elections.

Funding

The SLOTS survey has previously been funded by the Neelan Tiruchelvam Trust, the UK National Institute for Health and Care Research (NIHR), The Asia Foundation in Sri Lanka, and others. Current fieldwork is financed by the IHP Public Interest Research Fund and others. The sponsors play no role in the study design, analysis, or interpretation of findings. Furthermore, the survey findings do not necessarily reflect the views or positions of past and present funders. Interested parties can contact IHP for more detailed data and results.