Whereas age-standardization adjusts for underlying differences in the age distribution of the combined male-female population, age/sex-standardized rates adjust for differences in the population distribution by both age and sex simultaneously.
Age/sex-standardized rates are NOT the same as sex-specific age-adjusted rates.
Like age, sex has a powerful influence on disease rates. Males and females have markedly different incidence, prevalence, and mortality rates for certain diseases and males have a shorter life expectancy than females.
Therefore, in order to fully account for these differences, researchers may want to adjust for both age and sex when making comparisons for some conditions.
The calculation for age/sex adjustment differs from age-standardization in that the individual age-specific rates are stratified by sex and are applied to the standard population stratified by sex.
The requirements for the calculation of age/sex standardized rates are:
Study population by age and sex
Standard population by age and sex
Formula
ei(f) is the number of events for females in age group i
ei(m) is the number of events for males in age group i
pi(f) is the number of females in age group i the study population
pi(m) is the number of males in age group i the study population
Pi(f) is the number of females in age group i in the Standard population
Pi(m) is the number of males in age group i in the Standard population
For each age stratum the expected number of events is the sum of the expected number of events for males plus the expected number of events for females in that stratum
Age-specific expected events= Ei
=[(ei(m) /pi(m) ) *Pi(m) ] + [ (ei(f) /pi(f) ) *Pi(f) ]
The age/sex Standardized Rate (per 100 000) is the sum of all expected events divided by the total standard population
= [ Sum(Ei)/Sum(Pi)] * 1000
You can use the z test for two proportions. The link below will do this test for you.
a statistical is a question that has a variety of answers, but a non-statistical question has only one answer. like if i say "how old am i?" that is a non-statistical question because there is only one answer. But if I say "How old are the 6th and 7th grade students in school?" that is a statistical question because there will be various answers.
t-test is the statistical test used to find the difference of mean between two groups
Random error.
A sample of a population is a subset of the population. The average of the population is a statistical measure for some variable of the population.
Characterisation is the character of a person or the way someone acts, standardisation is the standard process of something that is the basic and or standing process
Explain the difference between capability and control.
You can use the z test for two proportions. The link below will do this test for you.
Basic Statistical Return is the full form of BSR code,
a statistical is a question that has a variety of answers, but a non-statistical question has only one answer. like if i say "how old am i?" that is a non-statistical question because there is only one answer. But if I say "How old are the 6th and 7th grade students in school?" that is a statistical question because there will be various answers.
t-test is the statistical test used to find the difference of mean between two groups
an approach to sampling that has the characteristics of being randomly selected and the use of probability theory to evaluate sample results. Whereas non-statistical sampling is therefore any sampling approach that does not have both of the characteristicss of statistical sampling. I hope this will help....
look for a paper being published in "The Oncologist" later this year (2008)
No. The primary difference between for profit and not-for-profit organizations is simply their income tax treatment by the IRS.
Random error.
Statistical: must have random sampling, allows you to generalize to the population from which you randomly selected. Practical: do the results hold for similar individuals? allows you to generalize to similar individuals
SQC or statistical quality control is concerned with using the 7-QC and 7-SUPP tools to monitor process outputs. Statistical process control, or SPC is concerned with monitoring the inputs of the process.