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Text Table 2.1 shows the change in the relationship between passenger counts and population for the ten most-frequented Canadian cities over the years 1973, 1993 and 1998.

Farm operators and farm families in Canada are a diverse group. Farm operators differ by age, experience, business expectations, size and scale. These differences account for the varying responses these farmers have to farm programs and other government policies. To determine these responses, a farm "typology" has been developed to take account of the factors influencing their behavior.

As the availability of both health utilization and outcome information becomes increasingly important to health care researchers and policy makers, the ability to link person-specific health data becomes a critical objective. This type of linkage of population-based administrative health databases has been realized in British Columbia. The database was created by constructing an historical file of all persons registered with the health care system, and then by probabilistically linking various program files to this 'coordinating' file. The first phase of development included the linkage of hospital discharge data, physician billing data, continuing care data, data about drug costs for the elderly, births data and deaths data. The second phase of development has seen the addition data sources external to the Ministry of Health including cancer incidence data, workers' compensation data, and income assistance data.

To reach their target audience efficiently, advertisers and media planners need information on which media their customers use. For instance, they may need to know what percentage of Diet Coke drinkers watch Baywatch, or how many AT&T customers have seen an advertisement for Sprint during the last week. All the relevant data could theoretically be collected from each respondent. However, obtaining full detailed and accurate information would be very expensive. It would also impose a heavy respondent burden under current data collection technology. This information is currently collected through separate surveys in New Zealand and in many other countries. Exposure to the major media is measured continuously, and product usage studies are common. Statistical matching techniques provide a way of combining these separate information sources. The New Zealand television ratings database was combined with a syndicated survey of print readership and product usage, using statistical matching. The resulting Panorama service meets the targeting information needs of advertisers and media planners. It has since been duplicated in Australia. This paper discusses the development of the statistical matching framework for combining these databases, and the heuristics and techniques used. These included an experiment conducted using a screening design to identify important matching variables. Studies evaluating and validating the combined results are also summarized. The following three major evaluation criteria were used; accuracy of combined results, statibility of combined results and the preservation of currency results from the component databases. The paper then discusses how the prerequisites for combining the databases were met. The biggest hurdle at this stage was the differences between the analysis techniques used on the two component databases. Finally, suggestions for developing similar statistical matching systems elsewhere will be given.

Text Table 2.1 shows the change in the relationship between passenger counts and population for the ten most-frequented Canadian cities over the years 1973, 1993 and 1998.

Farm operators and farm families in Canada are a diverse group. Farm operators differ by age, experience, business expectations, size and scale. These differences account for the varying responses these farmers have to farm programs and other government policies. To determine these responses, a farm "typology" has been developed to take account of the factors influencing their behavior.

As the availability of both health utilization and outcome information becomes increasingly important to health care researchers and policy makers, the ability to link person-specific health data becomes a critical objective. This type of linkage of population-based administrative health databases has been realized in British Columbia. The database was created by constructing an historical file of all persons registered with the health care system, and then by probabilistically linking various program files to this 'coordinating' file. The first phase of development included the linkage of hospital discharge data, physician billing data, continuing care data, data about drug costs for the elderly, births data and deaths data. The second phase of development has seen the addition data sources external to the Ministry of Health including cancer incidence data, workers' compensation data, and income assistance data.

To reach their target audience efficiently, advertisers and media planners need information on which media their customers use. For instance, they may need to know what percentage of Diet Coke drinkers watch Baywatch, or how many AT&T customers have seen an advertisement for Sprint during the last week. All the relevant data could theoretically be collected from each respondent. However, obtaining full detailed and accurate information would be very expensive. It would also impose a heavy respondent burden under current data collection technology. This information is currently collected through separate surveys in New Zealand and in many other countries. Exposure to the major media is measured continuously, and product usage studies are common. Statistical matching techniques provide a way of combining these separate information sources. The New Zealand television ratings database was combined with a syndicated survey of print readership and product usage, using statistical matching. The resulting Panorama service meets the targeting information needs of advertisers and media planners. It has since been duplicated in Australia. This paper discusses the development of the statistical matching framework for combining these databases, and the heuristics and techniques used. These included an experiment conducted using a screening design to identify important matching variables. Studies evaluating and validating the combined results are also summarized. The following three major evaluation criteria were used; accuracy of combined results, statibility of combined results and the preservation of currency results from the component databases. The paper then discusses how the prerequisites for combining the databases were met. The biggest hurdle at this stage was the differences between the analysis techniques used on the two component databases. Finally, suggestions for developing similar statistical matching systems elsewhere will be given.