Objective To explore the usefulness of incidence–prevalence–mortality (IPM) models in improving estimates of disease epidemiology. Methods Two artificial and four empirical data sets (for breast, prostate, colorectal, and stomach cancer) were employed in IPM models. Findings The internally consistent artificial data sets could be reproduced virtually identically by the models. Our estimates often differed considerably from the empirical data sets, especially for breast and prostate cancer and for older ages. Only for stomach cancer did the estimates approximate to the data, except at older ages. Conclusion There is evidence that the discrepancies between model estimates and observations are caused both by data inaccuracies and past trends i...
Background: The epidemiology of a disease describes numbers of people becoming incident, being preva...
Background. One of the epidemiologist's most basic tasks Is estimation of disease occurrence. T...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...
Objective To explore the usefulness of incidence-prevalence-mortality (IPM) models in improving esti...
textabstractBackground. Health policy and planning depend on quantitative data of disease epidemiolo...
BACKGROUND: Health policy and planning depend on quantitative data of disease epidemiology. Ho...
Background Population-based cancer registries are required to calculate cancer incidence in a geogr...
Population-based cancer registries are required to calculate cancer incidence in a geographical area...
Age-period-cohort models have been used to examine and forecast cancer incidence and mortality for o...
Using the simulation model context we checked the consistency of incidence, prevalence and mortality...
textabstractWe explored these two research questions on the basis of empirical data for two common ...
OBJECTIVE: To determine if introducing age as another explanatory variable in an ecological regressi...
Background In order to monitor the impact of health policy, morbidity estimates must be timely and r...
BACKGROUND: Morbidity estimates between different GP registration networks show large, unexplained v...
Background: Morbidity estimates between different GP registration networks show large, unexplained v...
Background: The epidemiology of a disease describes numbers of people becoming incident, being preva...
Background. One of the epidemiologist's most basic tasks Is estimation of disease occurrence. T...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...
Objective To explore the usefulness of incidence-prevalence-mortality (IPM) models in improving esti...
textabstractBackground. Health policy and planning depend on quantitative data of disease epidemiolo...
BACKGROUND: Health policy and planning depend on quantitative data of disease epidemiology. Ho...
Background Population-based cancer registries are required to calculate cancer incidence in a geogr...
Population-based cancer registries are required to calculate cancer incidence in a geographical area...
Age-period-cohort models have been used to examine and forecast cancer incidence and mortality for o...
Using the simulation model context we checked the consistency of incidence, prevalence and mortality...
textabstractWe explored these two research questions on the basis of empirical data for two common ...
OBJECTIVE: To determine if introducing age as another explanatory variable in an ecological regressi...
Background In order to monitor the impact of health policy, morbidity estimates must be timely and r...
BACKGROUND: Morbidity estimates between different GP registration networks show large, unexplained v...
Background: Morbidity estimates between different GP registration networks show large, unexplained v...
Background: The epidemiology of a disease describes numbers of people becoming incident, being preva...
Background. One of the epidemiologist's most basic tasks Is estimation of disease occurrence. T...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...