Reliable causal inference based on observational studies is seriously threatened by unmeasured confounding.
What is unmeasured cofounding?
- By definition, an unmeasured confounder is a variable that is connected to both the exposed and the result and could explain the apparent observed link.
- The validity of interpretation in observational studies is threatened by unmeasured confounding. The use of negative control group to reduce unmeasured confounding has grown in acceptance and popularity in recent years.
Although they've been utilised mostly for bias detection, negative controls have a long history in laboratory sciences and epidemiology of ruling out non-causal causes. A pair of negative control exposure and outcome variables can be utilised to non-parametrically determine the average treatment effect (ATE) from observational data that is vulnerable to uncontrolled confounding, according to a recent study by Miao and colleagues.
Reliable causal inference based on observational studies is seriously threatened by unmeasured confounding.
Learn more about unmeasured confounding here:
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The answer is, 25z^4+30z^3+29z^2+12z+4
Or z(z(z(25z+30)+29)+12)+4
Answer:
The nomber of people can attend a dinner that costs $131. 50 is 14.
Step-by-step explanation:
With the information provided, it can be said that the total cost of a dinner would be equal to the initial fee plus the result of multiplying the price per person for the number of people, which can be expressed as:
c=16+8.25x, where:
c is the total cost of he dinner
x is the number of people
Now, you can replace c with 131.50 that is the cost of a dinner and solve for x to find the number of people that can attend:
131.50=16+8.25x
131.50-16=8.25x
115.50=8.25x
x=115.50/8.25
x=14
According to this, the answer is that the nomber of people can attend a dinner that costs $131.50 is 14.
the answer is 6/13 because 12/26 reduces so the answer is 6/13
