The Nielsen Comapny (us), LLC

Joshua T Deragon

Denis Voytenko

Paul J Chimenti

Thomas Harrington

Jack Barbey

David J Kurzynski

William Deshong

Brett Gebhardt

Horalia Armas

Methods, apparatus, systems, and articles of manufacture to determine an additive reach adjustment factor for audience measurement are disclosed. An example apparatus for additive reach adjustment includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to identify a first probability, the first probability associated with a population tuning to a marketing campaign, the tuning including missing data, identify a second probability, the second probability associated with the population not tuning to the marketing campaign or the tuning including missing data, determine an additive reach adjustment based on a compound probability and a no-tuning probability, the compound probability and the no-tuning probability determined using the first probability and the second probability, and credit a population exposed to the marketing campaign to include missing impressions based on the additive reach adjustment.

Methods and apparatus to determine additive reach adjustment factors for audience measurement

An example apparatus includes a distance matrix generator to determine a number of remapping combinations corresponding to a first and a second household demographic model, generate (a) a first age-based household demographic model and a second age-based household demographic model and (b) a third age-based household demographic model and a fourth age-based household demographic model, generate a first distance matrix corresponding to the first and the third age-based household demographic model, and generate a second distance matrix corresponding to the second and the fourth age-based household demographic model, a distance matrix identifier to determine a first and a second reassignment distance and a person identification assigner to assign a person identification number of a first person corresponding to the first household to a second person corresponding to the second household based on the first distance matrix or the second distance matrix.

Methods, systems, articles of manufacture and apparatus to remap household identification

An example apparatus includes a distance matrix generator to determine a number of remapping combinations corresponding to a first and a second household demographic model, generate (a) a first age-based household demographic model and a second age-based household demographic model and (b) a third age-based household demographic model and a fourth age-based household demographic model, generate a first distance matrix corresponding to the first and the third age-based household demographic model, and generate a second distance matrix corresponding to the second and the fourth age-based household demographic model; a distance matrix identifier to determine a first and a second reassignment distance; and a person identification assigner to assign a person identification number of a first person corresponding to the first household to a second person corresponding to the second household based on the first distance matrix or the second distance matrix.

Methods, apparatus, systems and articles of manufacture are disclosed to reduce a remapping error. An example apparatus includes a distance matrix generator to generate a distance matrix corresponding to a first household demographic model and a second household demographic model. The example apparatus also includes a distance matrix identifier to determine a reassignment distance of the distance matrix. The example apparatus also includes a person identification assigner to, in response to the reassignment distance being less than a reassignment threshold, assign a person identification number of a first person of the first household to a second person of the second household based on the distance matrix.

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Oldsmar, FL, United States of America

Joshua T Deragon