similar to: Large F-value and small P-value

Displaying 5 results from an estimated 5 matches similar to: "Large F-value and small P-value"

2011 Nov 18
1
How to fill irregular polygons with patterns?
Hi, I'm looking the best way to fill irregular polygons with patterns, Something like the function grid.pattern do, but my case is with irregular polygons. Whit this script I can get it, but I'm looking for an "elegant" solution.. library(grid) grid.polygon(x=c(0.2, 0.8, 0.6, 0.6, 0.8, 0.2), y=c(0.2, 0.2, 0.3, 0.5, 0.7,0.7), gp=gpar(fill="grey",
2003 Oct 04
2
(no subject)
Dear all, I have the following question. I have to fit the hierarchical model for the hypothesis concern the individual-level effects by controlling for the individual -level attributes and national-level contextual effects on individuals by using R. O have to obtain the estimates of the impact of the second-level (national: GDP per capita) effects on individuals ( in this instance the impact
2020 Apr 07
2
Adding a new External Suite to test-suite
Hi Johannes, > All the use cases sound reasonable but why do we need these kind of "weird files" to do this? > > I mean, why would you train or measure something on single definition translation units and not on the original ones, potentially one function at a time? I think that's the fundamental question :) The short answer is that it is hard to compile the files from
2006 Aug 29
0
how to contrast with factorial experiment
Hello, R experts, If I understand Ted's anwser correctly, then I can not contrast the mean yields between sections 1-8 and 9-11 under "Trt" but I can contrast mean yields for sections 1-3 and 6-11 because there exists significant interaction between two factors (Trt:section4, Trt:section5). Could I use the commands below to test the difference between sections 1-3 and 6-11 ?
2011 Nov 11
2
Estimating IRT models by using nlme() function
Hi, I have a question about estimating IRT models by using nlme, not just rasch model, but also other models. Behavior Research Methods <http://www.springerlink.com/content/1554-351x/> Volume 37, Number 2 <http://www.springerlink.com/content/1554-351x/37/2/>, 202-218, DOI: 10.3758/BF03192688 Using SAS PROC NLMIXED to fit item response theory models (2005). Ching-Fan