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Hello, I have conducted an SEM in which the resultant standardized path coefficients are much higher than would be expected from the raw correlation matrix. To explore further, I stripped the model down to a simple bivariate relationship between two variables (NDVI, and species richness), where it's my understanding that the SEM's standardized path coefficient should equal the correlation

What is the difference when including or not including the intercept when using lm()? x.noint <- lm(weight ~ group - 1))# omitting intercept x <- lm(weight ~ group)) This has nothing to do with forcing the intercept to 0, correct? Thank you kindly, Michael [[alternative HTML version deleted]]

...ed measures (measurements are equally spaced in time, subjects are measured several times a year). I need to allow slope and intercept vary. SAS codes are: proc mixed data = survey method=reml; class subject var1 var3 var2 time; model score = var2 score_base var4 var5 var3 var6 var7 var1 time/ noint solution; random intercept timecontinious / subject=subject type=un g gcorr v vcorr; run; Thank you a lot! [[alternative HTML version deleted]]

...plain > > You can use the hangupcause variable which us the pri cause code > supplied when a call is ended over a PRI line. For example this is the > maco we use to dial a number over PRI. > > [macro-pridial] > exten => s,1,GotoIf($["${ARG1:0:2}" != "00"]?noint) > exten => s,n,Set(DENYINT=${DB(denyinternational/${CALLERIDNUM})}) > exten => s,n,GotoIf($[ "${DENYINT}" = "yes" ]?congestion) > exten => s,n(noint),Set(BLOCKCID=${DB(blockcid/${CALLERIDNUM})}) > exten => s,n,GotoIf($[ "${BLOCKCID}" = "ye...

...m is that I obtain different degrees of freedom compared to one in the book. Could it be sum of squares problem (type III vs. type I)? Milliken & Johnson use SAS for calculations and this is program the used: proc mixed data=mmacov method=type3; class type; model time=type bstime*type/solution noint. My R code is: LME.1=lme(time~bstime:type+type-1,data=CCE,random=~1|type) and summary is: Value Std.Error DF t-value p-value typeBlue M&M 18.0 18.5 0 0.97 NaN typeButton...

...t this SAS syntax with PROC NLMIXED. nlme or lme4? or they both would work well? Original SAS syntax (if it makes any difference?)..... proc mixed data=bi_meta method=reml cl ; /* option cl will give confidence intervals */ class study_id modality; model logit dis*modality non_dis*modality / noint cl df=1000, 1000, 1000, 1000, 1000, 1000; random dis non_dis / subject=study_id type=un ; repeated / group=rec; parms / parmsdata=cov hold=4 to 91; Best regards to all, Pedro Emmanuel Brasil Chagas disease clinical research laboratory IPEC-FIOCRUZ Rio de Janeiro - Brasil [[alternative HTML vers...

...nalysis of the recent Kirwan et al paper in Ecology [9(80), 2032-2032]. The SAS code is available but am having troubles getting the R equivalents. The SAS code is: *Model 5 - Species-specific interaction coefficients; PROC GLM; where N=150; MODEL YIELD=G1 G2 L1 L2 G1INT G2INT L1INT L2INT M / NOINT SOLUTION; *calculate the pairwise interaction coefficients; estimate 'g1*g2' g1int 1 g2int 1; estimate 'g1*l1' g1int 1 l1int 1; estimate 'g1*l2' g1int 1 l2int 1; estimate 'g2*l1' g2int 1 l1int 1; estimate 'g2*l2' g2int 1 l2int 1; estimate 'l1*l2' l1in...

...ructured matrix differs across groups; * Specified in the RANDOM statement by the GROUP=grp option; title 'RANDOM COEFFICIENT MODEL WITH DIAGONAL WITHIN-PATIENT'; title1 'DIFFERENT D MATRIX FOR BOTH GENDERS'; proc mixed method=ml data=dent1; class pt grp; model y = grp grp*t / noint solution; random intercept t / type=un group=grp subject=pt g gcorr v vcorr; run; The key to specifying different covariance structure for the random effects seems to be the highlighted portion in the code. What would be it's equivalent in R? In R, I tried the following Model1 &lt...

    Hello Everyone,   I'm trying to use SAS to replicate some results obtained in R. I was wondering if anyone call tell me the SAS equivalent of the code that appears below.   fm.glm.x <- glm(resp ~ . - 1, data = as.data.frame(mm.x),  na.action = na.exclude, family = binomial(link = "probit")) summary(fm.glm.x) Thanks,   Paul [[alternative HTML version deleted]]

...syntax. It seems that I was able to do it for part of the model, but a few things are still different. It is a 2-level bivariate model (some call it a pseudo-3-level model). PROC MIXED DATA=psdata.bivar COVTEST METHOD = ml; CLASS cluster_ID individual_id variable_id ; MODEL y = Dp Dq / SOLUTION NOINT; RANDOM Dp Dq / SUBJECT = cluster_ID TYPE=UN G GCORR; REPEATED variable_id / SUBJECT = individual_ID(cluster_ID) TYPE=UN R RCORR; RUN; Here is my try: dta = sqlQuery(odbcConnect("sasodbc", believeNRows=FALSE), "select * from psdata.bivar") v = lme(Y~Dp+Dq-1, data=dta, random=...

Hi, I am not a statistics expert, so I have this question. A linear model gives me the following summary: Call: lm(formula = N ~ N_alt) Residuals: Min 1Q Median 3Q Max -110.30 -35.80 -22.77 38.07 122.76 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 13.5177 229.0764 0.059 0.9535 N_alt 0.2832 0.1501 1.886 0.0739

...= T1; > + } > + > + // Not every type can be vectorized... > + if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) || > + !(VectorType::isValidElementType(T2) || T2->isVectorTy())) { > + continue; > + } > + > + if (NoInts&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy())) { > + continue; > + } > + > + if (NoFloats&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy())) { > + continue; > + } > + > + if (T1->getPrimitiveSi...

...t; + // Not every type can be vectorized... > > + if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) || > > + !(VectorType::isValidElementType(T2) || T2->isVectorTy())) { > > + continue; > > + } > > + > > + if (NoInts&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy())) { > > + continue; > > + } > > + > > + if (NoFloats&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy())) { > > + continue; > > + } > > + &g...

Tobias, et al., Attached is the my autovectorization pass. I've fixed a bug that appears when using -bb-vectorize-aligned-only, fixed some 80-col violations, etc., and at least on x86_64, all test cases pass except for a few; and all of these failures look like instruction-selection bugs. For example: MultiSource/Applications/ClamAV - fails to compile shared_sha256.c with an error: error in

Tobias, I've attached the latest version of my autovectorization patch. I was able to add support for using the ScalarEvolution analysis for load/store pairing (thanks for your help!). This led to a modest performance increase and a modest compile-time increase. This version also has a cutoff as you suggested (although the default value is set high (4000 instructions between pairs) because

...lementptr inbounds [13 x i16]* %ai.i.i.i.i, i32 0, i32 11 %scevgep.i217.i.i.i.i = getelementptr [13 x i16]* %bi.i.i.i.i, i32 0, i32 12 %scevgep.i194.i.i.i.i = getelementptr [13 x i16]* %ai.i.i.i.i, i32 0, i32 12 br label %do.body.i do.body.i: ; preds = %noint.i, %if.then58.i %expon.0.i = phi i32 [ 0, %if.then58.i ], [ %expon.1.i, %noint.i ] %p.0.i = phi i16* [ getelementptr inbounds ([13 x [10 x i16]]* @etens, i32 0, i32 8, i32 0), %if.then58.i ], [ %add.ptr.i, %noint.i ] %m.0.i = phi i16 [ 16, %if.then58.i ], [ %shr492.i, %noint.i ] call fastcc...

...T2 = T1; > + } No braces needed. > + > + // Not every type can be vectorized... > + if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) || > + !(VectorType::isValidElementType(T2) || T2->isVectorTy())) > + return false; > + > + if (NoInts&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy())) > + return false; > + > + if (NoFloats&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy())) > + return false; > + > + if (T1->getPrimitiveSizeInBits()> VectorBits/2 ||...

.... > > > + > > + // Not every type can be vectorized... > > + if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) || > > + !(VectorType::isValidElementType(T2) || T2->isVectorTy())) > > + return false; > > + > > + if (NoInts&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy())) > > + return false; > > + > > + if (NoFloats&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy())) > > + return false; > > + > > + if (T1->getPrimitiveSize...

On Mon, 2011-11-21 at 21:22 -0600, Hal Finkel wrote: > On Mon, 2011-11-21 at 11:55 -0600, Hal Finkel wrote: > > Tobias, > > > > I've attached an updated patch. It contains a few bug fixes and many > > (refactoring and coding-convention) changes inspired by your comments. > > > > I'm currently trying to fix the bug responsible for causing a compile

.... > > > + > > + // Not every type can be vectorized... > > + if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) || > > + !(VectorType::isValidElementType(T2) || T2->isVectorTy())) > > + return false; > > + > > + if (NoInts&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy())) > > + return false; > > + > > + if (NoFloats&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy())) > > + return false; > > + > > + if (T1->getPrimitiveSize...