How Nigeria’s 2015 presidential election outcome was forecasted with geodemographics and public sentiment analytics

In 2015, Nigeria held one of the most fiercely contested presidential elections in the nation’s recent democratic history. The outcome of the election was expected to exert significant influence on democratic practices on the African continent. The stiffness of the contest also meant that it was difficult to predict the likely winner of the election. This paper summarizes how an empirical approach was used to forecast the outcome of the election by modeling public sentiment data-set using a geodemographic framework. Results indicate that the main electorates that determined the outcome of the election were situated in thirteen battleground states. Additionally, results showed that two years before the presidential election, Goodluck Jonathan’s public approval ratings on corruption, insecurity, and the economy (the main drivers of the 2015 election) had nose-dived across many of the battleground states. This eventually contributed toward his loss

Cognitive Test Scores in UK Biobank:Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants

UK Biobank includes 502,649 middle- and older-aged adults from the general population who have undergone detailed phenotypic assessment. The majority of participants completed tests of cognitive functioning, and on average four years later a sub-group of N = 20,346 participants repeated most of the assessment. These measures will be used in a range of future studies of health outcomes in this cohort. The format and content of the cognitive tasks were partly novel. The aim of the present study was to validate and characterize the cognitive data: to describe the inter-correlational structure of the cognitive variables at baseline assessment, and the degree of stability in scores across longitudinal assessment. Baseline cognitive data were used to examine the inter-correlational/factor-structure, using principal components analysis (PCA). We also assessed the degree of stability in cognitive scores in the subsample of participants with repeat data. The different tests of cognitive ability showed significant raw inter-correlations in the expected directions. PCA suggested a one-factor solution (eigenvalue = 1.60), which accounted for around 40% of the variance. Scores showed varying levels of stability across time-points (intraclass correlation range = 0.16 to 0.65). UK Biobank cognitive data has the potential to be a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population