PharmD Info

A continuous variable is a variable whose value is obtained by measuring.

Examples: height of students in class
weight of students in class
time it takes to get to school
distance traveled between classes

what is probabilistic analysis? how to do?
In most models, each parameter is assigned a point estimate value. In probabilistic sensitivity analysis, rather than assigning a single value to each parameter, computer software (such as Crystal Ball, TreeAge, WinBUGS or other software) is used to assign a distribution to all parameters in the model. The ranges are determined by: The average value, The standard deviation, The ‘shape’ of the spread of data. Care is taken to ensure that all parameters remain practical. Each time the model is run, the software will be able to randomly ‘select’ one value for each parameter and record the model’s results. The results are typically presented using a cost-effectiveness scatter plane, where each iteration is plotted on a chart showing the incremental cost and incremental effectiveness of the intervention in question

sensitivity analyses study how various sources of uncertainty in a mathematical model contribute to the model's overall uncertainty.

1.EXAMPLE FOR ONE WAY SENSITIVITY ANALYSIS:

Suppose that a researcher would like to test which parameters have the greatest influence on a model’s results. In this case, each parameter in the model (or, at least, each of the key parameters) could be changed by a specific amount. Say, for example, that all parameters were to be increased and decreased by 20% of their original value. For each parameter change, the researcher might record the percentage impact on the model’s main outcome, which can be shown graphically

Probabilistic analysis is based on Monte Carlo simulations. Examines the impact on the results of the analysis when variables are varied simultaneously according to predefined distributions.
Advantages:Permits varying all parameters in the model simultaneously and enables calculation of the expected value and variance of decision variables. Uses information from clinical trials on distributions of effect size.
Disadvantages:Can only handle uncertainty in data inputs. It has also been criticised on the basis that it introduces further assumptions into the model – in particular, the choice of distribution to represent uncertainty.

A well-designed pharmacoeconomic analysis involves 10 steps:
(1) defining the problem
(2) determining the study's perspective
(3) determining the alternatives and outcomes
(4) selecting the appropriate pharmacoeconomic method
(5) placing monetary values on the outcomes
(6) identifying study resources
(7) establishing the probabilities of the outcomes
(8) applying decision analysis
(9) discounting costs or performing a sensitivity or incremental cost analysis
(10) presenting the results, along with any limitations of the study.

2.Sensitivity analysis is performed for all key parameters in an analysis, in order to test the validity and robustness of the conclusion.

In probabilistic sensitivity analysis, rather than assigning a single value to each parameter, computer software (such as Crystal Ball, TreeAge, WinBUGS or other software) is used to assign a distribution to all parameters in the model. The ranges are determined by: The average value, The standard deviation, The ‘shape’ of the spread of data. Care is taken to ensure that all parameters remain practical. Each time the model is run, the software will be able to randomly ‘select’ one value for each parameter and record the model’s results. The results are typically presented using a cost-effectiveness scatter plane, where each iteration is plotted on a chart showing the incremental cost and incremental effectiveness of the intervention in question.

Sensitivity analysis (pharmacoeconomics) Examining the changes in results when key variables are varied in an economic model. A cost-effectiveness analysis (CEA) is one of the key tools of economic evaluation. ... Sensitivity analysis (SA) suggests ways to calculate and evaluate this uncertainty

Sensitivity Analysis is a tool used in financial modeling to analyze how the different values of a set of independent variables affect a specific dependent variable under certain specific conditions. In general, Sensitivity Analysis is used in a wide range of fields, ranging from biology and geography to economics and engineering.