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Selection of initial model input parameters is an important step during model development. Input parameters are typically chosen to represent characteristics of the entire population: transitional probabilities (initiation, cessation, quitting, switching) and health outcome (mortality and/or morbidity rates).

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The initial values of these parameters are typically estimated from sources representative of the population, such as complex probability-based surveys or census data.  JirashowSummaryfalseserverIssue Tracker (JIRA)serverId85506ce4-3cb3-3d91-85ee-f633aaaf4a45keyTOBA-650

Transitional Probabilities 

Transition probabilities are typically chosen to represent characteristics of the population of interest (e.g. initiation, cessation, quitting, switching). Transition probabilities determine the rate at which the population changes with respect to time during the period of interest. For example, one might be interested in projecting the health impact of introducing a new tobacco product to the US population for a period of 50 years starting with the year 2000; transition probabilities govern transition between tobacco use behavior as well as health outcome during the projection period (50 years, in this example). The following figure shows different transition for a 2-products model developed by the FDA; each letter represents a transitional probability representing transitions from tobacco use behaviors over time.  

In the figure,

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a represents the probability of initiating product 1; b represents the probability of initiating product 2; and e represents the probability of initiating both productsThe figure below illustrates transitional probabilities for a two-product model. Transition probabilities are estimated from population surveys and other sources, and they are typically tabulated by sex, age and race. In some models, these are constant during the entire simulation period, but they could also change over time. 

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Example
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