SAS Support Communities

lauramb · ‎05-08-2018

Thanks, I'll look into adapting it for a 12 months time series analysis. Thanks!

lauramb · ‎05-08-2018

Hello everyone, I'm using SAS/STAT 14.3 and I was requested to do some basic (moving average) forecasting with time series data. I know it would be super easy if I had SAS/ETS, but unfortunately I'm a stat person. I was wondering if I could adapt some of the stat proc to do moving average. Or someone had a nice macro I could borrow. Thanks!

lauramb · ‎01-30-2018

There was an easier way...

lauramb · ‎01-29-2018

Hello everyone, I'm new to SAS and I have a few doubts about how to check for the assumption in a two-way ANOVA. For what I understand proc univariate looks at the distribution of the variable, not the residuals. So i have this general script that I put together looking at different posts in SAS cummunities. Is for a two way anova with interactions with two independent variables (A and B) and a response variable (Y). PROC glm DATA=data1; class A B; model Y= A B A*B; output out = resid p=predicted rstudent=rstd residual=res; run; quit; Proc gplot data = resid; /*Homocedasticity*/ plot rstd* (predicted); run; proc univariate data = resid normal; /*Normality*/ var res; histogram/normal; run; I don't know if this is the most parsimonious way to do this or there is a statement inside MIXED or GLM that I'm missing? How can I include a QQplot of the sample vs theoretical quantiles? Thanks for all your help! Laura

lauramb · ‎01-12-2018

Thanks all for your help!

lauramb · ‎01-11-2018

Hi everyone I'm new to SAS so my question may be quite basic: I have a blood test result (y) that follows the following relationship with a drug concentration (x): Y = B0 + B1*X**0.5 As I understand this is a linear relationship for the parameters (https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_nlin_sect003.htm) so the regression should be done using a linear regression model. I have used proc reg but with linear Y functions. As I understand the code for the linear regression is: proc reg data=dataser; var X**0.5; model Y=X; run; Is that correct? If I have the data of two groups (patients vs control) how can I compare the regression coefficients for both groups? Thanks for your help

lauramb · ‎12-18-2017

My confusion comes from the fact that I have two diseases, and the risk ratios are defined as the presence of disease B on the sub-population with disease A (A+) versus the presence of disease B on the sub-population without A (A-). Both sub-populations add up to the same population. I was thinking about standardizing the rate of sub-population A+ and A- to that of the general population, but I don't know if that makes any sense being that both come from the same population. Another option is to restrict the general population to the age at risk for the diseases. But this is not very precise.

lauramb · ‎12-18-2017

Hello there, I have the data: number of cases of disease A and disease B by age in a population and the census of that population. I also know which cases present with both diseases. My hypothesis is that both diseases are not related so I'm doing an equivalence test for the risk of having disease B if you have disease A. Mainly: B+A+/A+ = B+A-/A- (the margin is the 20% of the incidence in the A- group). What I have so far is: proc freq data = datas order=data; tables A*B/norow nocol nopercent riskdiff(equiv margin=0.0002); weight counts; run; I'm using counts because I have number of cases in the population and total population size, so I'm estimating the non diseased population from those numbers. My problem is that the probability for both diseases increases with age, so I need to to remove the age factor from my analysis. Is there a way to remove the co-variate from this model? Because I was thinking about standardization, but all the data comes from the same population. Any thoughts?

lauramb · ‎10-24-2017

Thanks for your help!

lauramb · ‎10-17-2017

Hi, I'm working with the following data involving incidence of a disease. My variables are YEAR, COUNTRY and INCIDENCE RATE (calculated on the basis of the total population of the country that year. So far I did a Cochran Armitage trend test to see if there is a significant trend over the years. The other thing I want to check is if I have a difference between countries. The thing is I don't have cases, just incidence rates. Basically I have the cases for the disease, but not for the not disease (if that makes any sense). Anyone knows how to work with this kind of data? i.e. only one value (freq) per variable (country)? Thanks! Any input will be welcomed!

Online Status	Offline
Date Last Visited	‎06-12-2018 05:13 PM

SAS Support Communities

Re: Forecasting/Time series analysis in SAS/STAT

Forecasting/Time series analysis in SAS/STAT

Re: Two-way ANOVA assumptions

Two-way ANOVA assumptions

Re: Linear regression comparison between groups

Linear regression comparison between groups

Re: Epidemiology-Equivalence testing to reject association between two...

Epidemiology-Equivalence testing to reject association between two dis...

Re: Incidence rates between populations

Incidence rates between populations

Re: Forecasting/Time series analysis in SAS/STAT

Re: Two-way ANOVA assumptions

Re: Linear regression comparison between groups

Re: Linear regression comparison between groups

Re: Linear regression comparison between groups

Linear regression comparison between groups

Re: Forecasting/Time series analysis in SAS/STAT

Forecasting/Time series analysis in SAS/STAT

Re: Two-way ANOVA assumptions

Two-way ANOVA assumptions

Re: Linear regression comparison between groups

Linear regression comparison between groups

Re: Epidemiology-Equivalence testing to reject association between two...

Epidemiology-Equivalence testing to reject association between two dis...

Re: Incidence rates between populations

Incidence rates between populations

Follow Us

What is...