Recently in the SAS Community Library: SAS' @StuartRogers provides a close look at the new Microsoft Entra Gallery application and details how it can be used.
data vs ; input patient cpevent$ vstest$ vsren vsorresu$; cards ; 100 base pr 78 min 100 scrn hr 72 /min 100 week1 sbp 70 mmhg 100 week7 dbp 110 mm 100 week21 weight 75 kg
100 fwp height 120 kg 100 base pr 78 min 100 scrn hr 79 /mn 100 week1 sbp 70 mmhg 100 week7 dbp 110 mm 100 week21 weight 80 pounds
100 fwp height 75 kg ;
Condition below
If VSTEST having same VSREN and VSORRESU for 4 consecutive visits then highlight those with flag as
"dulipcate record"
Based on above condition and data , create a flag
Please anyone help me .....
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How to create a tabulated report based on data:
Column CATEGORY in H means a horizontal report. TITLE_LEVELS indicate how many levels of title there are. TITLE_LEVEL1 is the main header, TITLE_LEVEL2 is the sub-header of TITLE_LEVEL1, and TITLE_LEVEL3 is the sub-header of TITLE_LEVEL2.
All columns are Character data type
proc tabulate data=datset;
class TITLE_LEVEL1 TITLE_LEVEL2 TITLE_LEVEL3 Column1 ;
table TITLE_LEVEL1*
TITLE_LEVEL2*TITLE_LEVEL3;
run;
i have data
i want
PFA
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I am currently analyzing the impact of an intervention on medication numbers using difference-in-difference analysis, but I have encountered several challenges. Following the SAS support instructions, I conducted the difference-in-difference analysis. However, I noticed a discrepancy between my results and SAS's example (Usage Note 61830: Estimating the difference in differences of means). In the example, the value of 'Mean Estimate' in 'Contrast Estimate Results' is identical to the 'Estimate' in 'Least Squares Means Estimate'. However, in my case, these values were different. I suspect this could be due to my use of the negative binomial distribution with a log link, resulting in exponential values. Consequently, I am unsure whether to rely on the 'Mean Estimate' in 'Contrast Estimate Results' or the 'Estimate' in 'Least Squares Means Estimate', and how to interpret the results." Contrast Estimate Results Label Mean Estimate Mean Confidence Limits L'Beta Estimate Standard Error diff in diff 1.51 1.49 0.41 0.0051 a*b Least Squares Means a b Estimate Standard Error z value Pr > |z| 1 1 0.77 0.00434 178.19 <.0001 1 0 0.03 0.00508 6.5 <.0001 0 1 0.72 0.00408 177.71 <.0001 0 0 0.40 0.00426 93.11 <.0001 Least Squares Means Estimate Effect Label Estimation Standard Error z value Pr > |z| time*hospitalize diff in diff 0.41 0.00509 81.01 <.0001
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I have a dataset structured as repeated measurement and Mixed model for repeated measurement is used for analysis. The standard code to get average change from baseline (note that here we are comparing baseline with the mean of the last 4 visits) and the associated p-value has been posted below. I wonder based on this, how can I test the non-inferiority using a margin of -1, e.g., change from baseline is greater than -1. The null hypothesis is that this change will be smaller or equal to -1. Can anyone suggest how to write SAS for this test? proc mixed data=mydata;
class id visit sex(ref='F');
model change = age sex baseline visit*baseline/ ddfm=kr fullx;
repeated visit / subject = id type = un;
lsmeans visit ;
estimate 'Average' Intercept 1 age 1 sex 0.5 0.5
visit 0 0 0 0 0 0.25 0.25 0.25 0.25 base & basemean
visit*base 0 0 0 0 0 &basemean1 &basemean1 &basemean1 &basemean1 / cl;
run;
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