2 independent factors 1 outcome

In summary, it is best to use the 21% chance of survival for more than 5 years when calculating the overall chance of success for a patient with both diseases. This is due to the fact that the diseases do contribute to the failure of treatment and that the disease with the lower 5 year survival rate is the determining factor.
  • #1
samy88
2
0
hello :)

i have a silly question and i keep confusing myself, hope someone can help me.

my friend has two diseases and I want to calculate a number to represent the chance of success (i.e. him surviving both diseases for more than 5 years)

disease A: chance of survival for more than 5 years, using certain treatment = 29%
disease B: chance of survival for more than 5 years, using the same treatment as A = 21%

both diseases are not related and don't affect each other but both contribute to failure of the treatment i.e. dying and not passing 5 years...

now, should I simply get the average of the two numbers (25%) or its supposed to be calculated in other way?

i keep confusing myself by thinking, the chance of passing 2 life threatening diseases at the same time should be lower than that!
 
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  • #2
samy88 said:
hello :)

disease A: chance of survival for more than 5 years, using certain treatment = 29%
disease B: chance of survival for more than 5 years, using the same treatment as A = 21%

both diseases are not related and don't affect each other but both contribute to failure of the treatment i.e. dying and not passing 5 years...

now, should I simply get the average of the two numbers (25%) or its supposed to be calculated in other way?

To say the two diseases don't affect each other is biologically unrealistic. The best statistics to apply would be based on subjects who had both diseases and had the same treatment (adjusted for many factors such as age, duration, severity of disease etc).

In the absence of this, the logic would be that the disease with lower 5 year survival would be determinative. That is, having a second disease with a better survival does nothing to mitigate having the more lethal disease. So, in the absence of any other data, the best estimate is 21% at best.
 
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1. What is meant by "2 independent factors 1 outcome"?

"2 independent factors 1 outcome" refers to a study or experiment that involves manipulating two different variables or factors to observe their effects on one outcome or result. The two factors are independent of each other, meaning that changes in one do not affect the other.

2. Why is it important to study 2 independent factors 1 outcome?

Studying 2 independent factors 1 outcome allows for a better understanding of the relationship between different variables and their impact on a specific outcome. This type of research can help identify potential causal factors and inform decision-making in various fields such as medicine, psychology, and social sciences.

3. How do you determine the influence of each independent factor on the outcome?

In a study with 2 independent factors 1 outcome, researchers use statistical analysis to determine the individual effects of each factor on the outcome. This can involve comparing groups with different levels of each factor, controlling for other variables, and calculating the correlation between the factors and the outcome.

4. Can there be more than 2 independent factors in a study?

Yes, there can be more than 2 independent factors in a study. The term "2 independent factors 1 outcome" simply refers to a specific type of study with two factors, but studies can have multiple independent variables and one outcome variable.

5. What are some examples of studies with 2 independent factors 1 outcome?

Examples of studies with 2 independent factors 1 outcome include experiments that test the effects of two different medications on blood pressure, the impact of different teaching methods on student performance, or the relationship between gender and income level on job satisfaction. These studies manipulate two factors while observing the effects on one outcome.

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