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My questions:;

My questions:

My questions;

2 corrected spelling

I'm attempting to calculate the mortality rates of AMI (acute myocardial infarction) in patients (cases) with high bloodpressure, between the years 2001 to 2008. For every case I have 2 matched controls that are healthy (i.e normal bloodpressure) and alsoblood pressure; matched for age, sex, socioeconomic status and demographics. Both controls and cases have been divided into 4 different age-groups. Thus far, I have calculated the number of events and person-years for both cases and controls.

I use the epitoolsepitools package in R and the ageadjust.direct function.

Here's the thing, I've done some age-standardised mortality rates in SAS with Proc STDRATE. I don't know exactly how the Proc STDRATE function works but my guess is that it somehow computes the mean age in all age-groups during the entire study period and subsequently works with these to estimate the IRR.

• Here's what i can't figure out. In the example in the age age-standardized description they've computed the mean persons-years for every age-group and and use that as the stdpop=standard instead of using the mean age of the the respective age-group. Intuitively I would say that the mean age of of every age-group would be more correct (since were trying to standardise standardise for age) then the persons-years.

• I's it theoretically correct to use my controls as the reference population as they are already matched for both age and sex or should I instead use the mean populations age as my reference population.

I'm attempting to calculate the mortality rates of AMI (acute myocardial infarction) in patients (cases) with high bloodpressure, between the years 2001 to 2008. For every case I have 2 matched controls that are healthy (i.e normal bloodpressure) and also matched for age, sex, socioeconomic status and demographics. Both controls and cases have been divided into 4 different age-groups. Thus far, I have calculated the number of events and person-years for both cases and controls.

I use the epitools package in R and the ageadjust.direct function.

Here's the thing, I've done some age-standardised mortality rates in SAS with Proc STDRATE. I don't know exactly how the Proc STDRATE function works but my guess is that it somehow computes the mean age in all age-groups during the entire study period and subsequently works with these to estimate the IRR.

• Here's what i can't figure out. In the example in the age-standardized description they've computed the mean persons-years for every age-group and use that as the stdpop=standard instead of using the mean age of the respective age-group. Intuitively I would say that the mean age of every age-group would be more correct (since were trying to standardise for age) then the persons-years.

• I's it theoretically correct to use my controls as the reference population as they are already matched for both age and sex or should I instead use the mean populations age as my reference population.

I'm attempting to calculate the mortality rates of AMI (acute myocardial infarction) in patients (cases) with high bloodpressure, between the years 2001 to 2008. For every case I have 2 matched controls that are healthy (i.e normal blood pressure; matched for age, sex, socioeconomic status and demographics. Both controls and cases have been divided into 4 different age-groups. Thus far, I have calculated the number of events and person-years for both cases and controls.

I use the epitools package in R and the ageadjust.direct function.

I've done some age-standardised mortality rates in SAS with Proc STDRATE. I don't know exactly how the Proc STDRATE function works but my guess is that it somehow computes the mean age in all age-groups during the entire study period and subsequently works with these to estimate the IRR.

• In the example in the age-standardized description they've computed the mean persons-years for every age-group and use that as the stdpop=standard instead of using the mean age of the respective age-group. Intuitively I would say that the mean age of every age-group would be more correct (since were trying to standardise for age) then the persons-years.

• I's it theoretically correct to use my controls as the reference population as they are already matched for both age and sex or should I instead use the mean populations age as my reference population.

1

# Estimating mortality rates with direct age-standardization

I'm attempting to calculate the mortality rates of AMI (acute myocardial infarction) in patients (cases) with high bloodpressure, between the years 2001 to 2008. For every case I have 2 matched controls that are healthy (i.e normal bloodpressure) and also matched for age, sex, socioeconomic status and demographics. Both controls and cases have been divided into 4 different age-groups. Thus far, I have calculated the number of events and person-years for both cases and controls.

I use the epitools package in R and the ageadjust.direct function.

I'll attach the example from the description in the epitools package:

population <- c(230061, 329449, 114920, 39487, 14208, 3052,
72202, 326701, 208667, 83228, 28466, 5375, 15050, 175702,
207081, 117300, 45026, 8660, 2293, 68800, 132424, 98301,
46075, 9834, 327, 30666, 123419, 149919, 104088, 34392,
319933, 931318, 786511, 488235, 237863, 61313)
population <- matrix(population, 6, 6,
dimnames = list(c("Under 20", "20-24", "25-29", "30-34", "35-39",
"40 and over"), c("1", "2", "3", "4", "5+", "Total")))
population

count <- c(107, 141, 60, 40, 39, 25, 25, 150, 110, 84, 82, 39,
3, 71, 114, 103, 108, 75, 1, 26, 64, 89, 137, 96, 0, 8, 63, 112,
262, 295, 136, 396, 411, 428, 628, 530)

count <- matrix(count, 6, 6,
dimnames = list(c("Under 20", "20-24", "25-29", "30-34", "35-39",
"40 and over"), c("1", "2", "3", "4", "5+", "Total")))
count

### Use average population as standard
standard<-apply(population[,-6], 1, mean)
standard