Methods and apparatus to determine synthetic respondent level data
Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. Example apparatus disclosed herein are to identify locations corresponding to monitored panelists, and when a first one of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates. Disclosed example apparatus are also to generate an affiliate probability based on the sum, and convert first data of households in the first one of the locations to a candidate receivability session based on the affiliate probability. Disclosed apparatus are further to generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data, and donate second data associated with a donor pool of first panelists to second panelists included in the seed panel, the second panelists associated with faulty media monitoring equipment.
1. An apparatus comprising:
at least one memory;
instruction in the apparatus; and
processor circuitry to execute the instructions to:
identify locations corresponding to monitored panelists;
when a first one of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates;
generate an affiliate probability based on the sum;
convert first data of households in the first one of the identified locations to a candidate receivability session based on the affiliate probability;
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel, the second panelists associated with faulty media monitoring equipment.
2. The apparatus of claim 1 , wherein the first data is at least one of tuning data or viewing data of the households.
3. The apparatus of claim 1 , wherein the processor circuitry is to generate the affiliate probability by normalizing the sum.
4. The apparatus of claim 1 , wherein the processor circuitry is to assign at least one of geography data or income data to the return path data based on demographics associated with the population.
5. The apparatus of claim 4 , wherein the processor circuitry is to:
select a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weight the seed panelists based on a universe estimate of media users.
6. The apparatus of claim 1 , wherein the processor circuitry is to at least one of replicate or down-sample seed panelists.
7. The apparatus of claim 1 , wherein the processor circuitry to:
compare a target rating to a computed rating determined based on the seed panel; and
adjust the seed panel based on the comparison to reduce an error between the target rating and the computed rating.
8. The apparatus of claim 1 , wherein the second data is the converted first data.
9. An apparatus comprising:
a station translator to:
identify locations corresponding to monitored panelists;
when a location of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates;
generate an affiliate probability based on the sum; and
convert first data of households in the location to a candidate receivability session based on the affiliate probability; and
a seed panel generator to:
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel, the second panelists associated with faulty media monitoring equipment.
10. The apparatus of claim 9 , wherein the first data is at least one of tuning data or viewing data of the households.
11. The apparatus of claim 9 , wherein the station translator is to generate the affiliate probability by normalizing the sum.
12. The apparatus of claim 9 , wherein the seed panel generator is to assign at least one of geography data or income data to the return path data based on demographics associated with the population.
13. The apparatus of claim 12 , wherein the seed panel generator is to:
select a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weight the seed panelists based on a universe estimate of media users.
14. The apparatus of claim 9 , wherein the seed panel generator is to at least one of replicate or down-sample seed panelists.
15. The apparatus of claim 9 , further including a seed panel optimizer to:
compare a target rating to a computed rating determined based on the seed panel; and
adjust the seed panel based on the comparison to reduce an error between the target rating and the computed rating.
16. The apparatus of claim 9 , wherein the second data is the converted first data.
17. A non-transitory computer readable medium comprising instructions which, when executed, cause one or more processors to at least:
identify locations corresponding to monitored panelists;
when a location of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates;
generate an affiliate probability based on the sum;
convert first data of households in the location to a candidate receivability session based on the affiliate probability;
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel when the second panelists are included in the seed panel, the second panelists corresponds to faulty media monitoring equipment.
18. The non-transitory computer readable medium of claim 17 , wherein the first data is at least one of tuning data or viewing data of the households.
19. The non-transitory computer readable medium of claim 17 , wherein the instructions cause the one or more processors to generate the affiliate probability by normalizing the sum.
20. The non-transitory computer readable medium of claim 17 , wherein the instructions cause the one or more processors to assign at least one of geography data or income data to the return path data based on demographics associated with the population.