Recent content by szm

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    proc import issue

    Hello, I have data with many missing observations in an excel file. Missing cells have a period ".". When using proc import, the "." is recognized as a level in subsequent analysis. However, when I paste the data directly in SAS, the "." is correctly identified as missing value. This affects...
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    Mixed model Beta distribution fit diagnostics

    Hello, I have a split-plot design and I want to test the effect of 2 factors on the disease incidence (continuous proportion). I am using Beta dist. which is appropriate for these data (bounded within 0-1). The fit statistics look OK (Pearson Chi-square/DF close to 1) Fit Statistics for...
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    proc fastclus output interpretation

    Thank you! That makes more sense now!
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    proc fastclus output interpretation

    Hello, I am using proc fastclus to perform k-means clustering. In Figure 42.2: Cluster Summary Table from the FASTCLUS Procedure, an R-square value is reported (please see link below)...
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    Mixed model LSMEANS vs ESTIMATE (BLUP)

    Thank you hlsmith for your thoughts and interest on this. I will try to email the author of the book, there is no reply to my post on SAS Communities. The std error for LSMEANS is 1.01 (p-value=0.0197) and for the BLUP is 0.83 (p-value=0.0005). The issue is that in another dataset, the...
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    Mixed model LSMEANS vs ESTIMATE (BLUP)

    I need to know why they are different. If the above BLUP estimate is the inference across the 5 locations, what is the LSMEANS then? Don't LSMEANS take into account the random effects and produce estimate of fixed effects across the 5 locations? That is what I thought. So which one should I...
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    Mixed model LSMEANS vs ESTIMATE (BLUP)

    Thank you hlsmith. I will read it thoroughly because I really need to understand the difference. It appears that LSMEAN compute the treatment effect across locations differently than the ESTIMATE (BLUP). I don't think I am doing something wrong, I follow the examples in chapter 6 in SAS for...
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    Mixed model LSMEANS vs ESTIMATE (BLUP)

    Randomized complete block design.
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    Mixed model LSMEANS vs ESTIMATE (BLUP)

    Hello, I am analyzing data from a multi-location trial (5 locations) to test the effectiveness of a treatment with 2 levels. The design is RCB with 3-4 replications in every location. I use the model below: proc mixed data=mydata; class location rep trt ; model Y=trt/ddfm=kr2 residual...
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    multi-location latin square design analysis

    Hello, I have a 5 x 5 Latin square design which is replicated 5 times within each location (same rows and columns in each location). The same design was used in 10 different locations and I was asked to perform a combined location analysis. I have done it before with other designs, such as RCB...
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    meta-analysis vs. random effect combined analysis

    I have data from 200 similar studies, all measuring the same effect of a continuous independent variable on the same continuous response. I say similar because the designs are different (split plot vs. rcbd) and the levels of the independent variable is not the same across all studies. I have...
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    permutations "partykit"

    Hello, I am new to R and I was reading about conditional decision trees. In the "party" package there is an option to select number of permutations (nresample=...). However, that is not the case with "partykit". So does it use permutations, even if it is a constant number and I can't...
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    split-split plot with continuous subplot variable

    Hello I am trying to analyze data from a split-split-plot design. The sub-plot is a continuous factor and since we suspect a non-linear relationship, the quadratic form needs to be tested as well. Factors: a-main plot-5 levels b-subplot-continuous c-sub-subplot-2 levels. To test the quadratic...
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    specify correct random effects

    Hi all, I have a CRD with 4 reps and 4 treatments (A, B, C, D). The study took place in 1 location for 3 years. I want to pool over years (so treat year as random effect). I am interested in main effects and up to 2-way interactions. So I am using the following model and random statement...
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    parameter estimate of categorical variable

    I run multiple regression with 2 continuous and 1 categorical variable (3 levels). SAS will hold the last level of the categorical variable and will not give an estimate. I know that this is the intercept. My question is how to calculate the interaction of the continuous variable with the 3rd...