Abstract: An example apparatus includes at least one memory, instructions, and at least one processor to execute the instructions to generate electronic mobile measurement data based on network communications received from first client devices, select attributes associated with the electronic mobile measurement data to include in a model, generate the model based on the attributes and a first portion of the electronic mobile measurement data, determine a percentage of a second portion of the electronic mobile measurement data that the model correctly associates with corresponding first users of the first client devices, and when the percentage satisfies a threshold determine: (a) when a second user operating a second client device is a primary user, and (b) when the user operating the second client device is a third user, and associate demographic information of the second user with the electronic mobile measurement data to reduce a misattribution error.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed.

Abstract: An example apparatus includes at least one memory, instructions, and at least one processor to execute the instructions to generate electronic mobile measurement data based on network communications received from first client devices, select attributes associated with the electronic mobile measurement data to include in a model, generate the model based on the attributes and a first portion of the electronic mobile measurement data, determine a percentage of a second portion of the electronic mobile measurement data that the model correctly associates with corresponding first users of the first client devices, and when the percentage satisfies a threshold determine: (a) when a second user operating a second client device is a primary user, and (b) when the user operating the second client device is a third user, and associate demographic information of the second user with the electronic mobile measurement data to reduce a misattribution error.

Abstract: An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to access first cookies and a plurality of user identifiers, the first cookies and the user identifiers corresponding to devices accessing media, determine an error between a first demographic estimate based on the first cookies forming a pattern and based on a second demographic estimate corresponding to the user identifiers, obtain impression information from a database proprietor, the impression information including second cookies, identify a subset of the second cookies that are associated with a same person based on the pattern, and associate impressions corresponding to the subset with the same person.

Abstract: Examples apparatus disclosed herein are to determine a plurality of weights based on a data structure having elements corresponding to pairings of ones of a plurality of demographic partition statistics and ones of a plurality of baseline demographic statistics obtained for a target population, the demographic partition statistics corresponding to a plurality of demographic partitions of a sample population, a first element of the data structure to combine a first one of the demographic partition statistics with a first one of the baseline demographic statistics of the target population based on a first value corresponding to a numerator term of an expression and a second value corresponding to a denominator term of the expression, the weights corresponding respectively to the demographic partitions of the sample population. Disclosed example apparatus are also to adjust the attribute data based on the weights to determine ratings data for the target population.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to access first cookies and a plurality of user identifiers, the first cookies and the user identifiers corresponding to devices accessing media, determine an error between a first demographic estimate based on the first cookies forming a pattern and based on a second demographic estimate corresponding to the user identifiers, obtain impression information from a database proprietor, the impression information including second cookies, identify a subset of the second cookies that are associated with a same person based on the pattern, and associate impressions corresponding to the subset with the same person.

Abstract: An example apparatus includes means for extracting characters from first cookies stored in a first memory space, the first cookies collected from client devices via network communications, and means for storing in a second memory space, a pattern of characters in association with a first demographic to indicate that the pattern of characters and the first demographic are both representative of a same first unique audience member, the storing being in response to determining that at least two of the first cookies (1) include the pattern of characters, and (2) correspond to the first demographic.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: An example apparatus includes at least one memory, instructions, and at least one processor to execute the instructions to generate electronic mobile measurement data based on network communications received from first client devices, select attributes associated with the electronic mobile measurement data to include in a model, generate the model based on the attributes and a first portion of the electronic mobile measurement data, determine a percentage of a second portion of the electronic mobile measurement data that the model correctly associates with corresponding first users of the first client devices, and when the percentage satisfies a threshold determine: (a) when a second user operating a second client device is a primary user, and (b) when the user operating the second client device is a third user, and associate demographic information of the second user with the electronic mobile measurement data to reduce a misattribution error.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: An example apparatus includes at least one processor and first memory comprising computer readable instructions that, when executed, cause the at least one processor to log an impression in second memory at an audience measurement entity based on a communication received from a computing device. The example computer readable instructions, when executed, cause the at least one processor to determine that a primary user of the computing device is not the user operating the computing device when a first probability score for the primary user does not satisfy a threshold, and in response to determining that the primary user is not the user operating the computing device, identify one of a plurality of secondary users as the user operating the computing device. The example computer readable instructions, when executed, cause the at least one processor to store demographic information of the user operating the computing device.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed.

Abstract: Examples apparatus disclosed herein are to determine a plurality of weights based on a data structure having elements corresponding to pairings of ones of a plurality of demographic partition statistics and ones of a plurality of baseline demographic statistics obtained for a target population, the demographic partition statistics corresponding to a plurality of demographic partitions of a sample population, a first element of the data structure to combine a first one of the demographic partition statistics with a first one of the baseline demographic statistics of the target population based on a first value corresponding to a numerator term of an expression and a second value corresponding to a denominator term of the expression, the weights corresponding respectively to the demographic partitions of the sample population. Disclosed example apparatus are also to adjust the attribute data based on the weights to determine ratings data for the target population.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage by a database proprietor are disclosed. An example method includes obtaining a count of media impressions occurring on a first type of computing device, a first portion of the media impressions corresponding to persons for whom demographic information is recognizable by a database proprietor and a second portion of the media impressions corresponding to persons for whom demographic information is unavailable to the database proprietor; and determining the demographic information for the second portion of the media impressions based on a first probability that media corresponding to the media impressions is accessed on the first type of computing device and based on a second probability that media is accessed on a second type of device.

Abstract: Methods, apparatus, systems and articles of manufacture to correct for bias in ratings data are disclosed. Example methods disclosed herein include accessing information specifying a set of population strata having corresponding strata demographic statistics capable of being combined to determine a first set of baseline demographic statistics for a sample population that corresponds to a second set of baseline demographic statistics for a target population. Disclosed example methods also include determining a set of weights corresponding respectively to the set of population strata that reduces bias between the second set of baseline demographic statistics for the target population and the first set of baseline demographic statistics for the sample population when the set of weights is applied to the strata demographic statistics to determine the first set of baseline demographic statistics for the sample population.

Abstract: An example apparatus includes means for extracting characters from first cookies stored in a first memory space, the first cookies collected from client devices via network communications, and means for storing in a second memory space, a pattern of characters in association with a first demographic to indicate that the pattern of characters and the first demographic are both representative of a same first unique audience member, the storing being in response to determining that at least two of the first cookies (1) include the pattern of characters, and (2) correspond to the first demographic.

Abstract: An example apparatus includes means for identifying a pattern in first cookies received via the Internet and stored in a storage device, the first cookies corresponding to devices accessing media via the Internet, means for determining an error between a first demographic estimate based on a potential pattern in the first cookies and a second demographic estimate based on user identifiers corresponding to the devices and received via the Internet, the means for determining the error to determine the potential pattern to be the pattern when the error is less than a threshold, means for accessing impression information received from a database proprietor via the Internet, the impression information including second cookies, and means for identifying a subset of the second cookies that are associated with a same person based on the pattern, the means for identifying the subset to associate impressions corresponding to the identified subset with the same person.