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week 8 compendium

*The author of this computation has been verified*

R Software Module: Ian.Holliday/rwasp_One Factor ANOVA.wasp (opens new window with default values)

Title produced by software: One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation: Fri, 26 Nov 2010 12:21:27 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2.htm/, Retrieved Fri, 26 Nov 2010 13:20:33 +0100

BibTeX entries for LaTeX users:

@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

2 36 2 56 3 48 1 32 1 44 2 39 2 34 1 41 3 50 1 39 3 62 2 52 1 37 2 50 2 41 2 55 1 41 3 56 2 39 1 52 1 46 1 44 2 41 3 50 2 50 1 44 2 52 2 54 2 44 3 52 2 37 2 52 2 50 1 36 2 50 2 52 3 55 1 31 2 36 1 49 2 42 2 37 2 41 2 30 2 52 1 30 2 44 2 66 1 48 3 43 1 57 1 46 1 54 2 48 2 48 1 62 1 58 2 58 2 62 2 46 1 34 3 66 2 52 1 55 1 55 2 57 1 56 2 55 3 56 2 54 2 55 3 46 1 52 2 32 1 44 2 46 1 59 2 46 2 46 3 54 3 66 2 56 2 59 2 57 2 52 2 48 2 44 1 41 1 50 1 48 3 48 2 59 2 34 2 46 2 54 1 55 2 54 2 59 2 44 1 54 2 52 3 66 2 44 1 57 1 39 1 60 1 45 2 41 2 50 3 39 2 43 2 48 2 37 3 58 1 46 3 43 1 44 2 34 2 30 2 50 1 39 2 37 1 55 3 41 2 39 2 36 1 43 3 50 2 55 1 43 1 60 1 48 1 30 2 43 3 39 2 52 2 39 1 39 2 56 1 59 1 46 2 57 1 50 2 54 1 50 3 60 3 59 3 41 2 48 2 59 2 60 1 56 1 51

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'George Udny Yule' @ 72.249.76.132

ANOVA Model
MVRBIQ ~ MC30VRB
means	1.5	-0.5	0	0.25	0.25	0.3	0.3	0.389	0.5	0.5	0	-0.5	0.2	0.4	-0.5	0.5	-0.5	0.417	0.375	0.167	0.5	0.1	0.5	0.357	0.25	0.5	1.25

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
MC30VRB	26	9.738	0.375	0.772	0.775
Residuals	126	61.138	0.485

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
31-30	-0.5	-3.446	2.446	1
32-30	0	-2.282	2.282	1
34-30	0.25	-1.613	2.113	1
36-30	0.25	-1.613	2.113	1
37-30	0.3	-1.467	2.067	1
39-30	0.3	-1.259	1.859	1
41-30	0.389	-1.194	1.972	1
42-30	0.5	-2.446	3.446	1
43-30	0.5	-1.201	2.201	1
44-30	0	-1.559	1.559	1
45-30	-0.5	-3.446	2.446	1
46-30	0.2	-1.359	1.759	1
48-30	0.4	-1.159	1.959	1
49-30	-0.5	-3.446	2.446	1
50-30	0.5	-1.021	2.021	1
51-30	-0.5	-3.446	2.446	1
52-30	0.417	-1.104	1.938	1
54-30	0.375	-1.238	1.988	1
55-30	0.167	-1.417	1.75	1
56-30	0.5	-1.151	2.151	1
57-30	0.1	-1.667	1.867	1
58-30	0.5	-1.512	2.512	1
59-30	0.357	-1.294	2.009	1
60-30	0.25	-1.613	2.113	1
62-30	0.5	-1.512	2.512	1
66-30	1.25	-0.613	3.113	0.701
32-31	0.5	-2.727	3.727	1
34-31	0.75	-2.196	3.696	1
36-31	0.75	-2.196	3.696	1
37-31	0.8	-2.086	3.686	1
39-31	0.8	-1.963	3.563	1
41-31	0.889	-1.888	3.666	1
42-31	1	-2.726	4.726	1
43-31	1	-1.846	3.846	1
44-31	0.5	-2.263	3.263	1
45-31	0	-3.726	3.726	1
46-31	0.7	-2.063	3.463	1
48-31	0.9	-1.863	3.663	1
49-31	0	-3.726	3.726	1
50-31	1	-1.742	3.742	1
51-31	0	-3.726	3.726	1
52-31	0.917	-1.826	3.659	1
54-31	0.875	-1.919	3.669	1
55-31	0.667	-2.111	3.444	1
56-31	1	-1.817	3.817	1
57-31	0.6	-2.286	3.486	1
58-31	1	-2.042	4.042	1
59-31	0.857	-1.959	3.674	1
60-31	0.75	-2.196	3.696	1
62-31	1	-2.042	4.042	1
66-31	1.75	-1.196	4.696	0.877
34-32	0.25	-2.032	2.532	1
36-32	0.25	-2.032	2.532	1
37-32	0.3	-1.904	2.504	1
39-32	0.3	-1.741	2.341	1
41-32	0.389	-1.671	2.448	1
42-32	0.5	-2.727	3.727	1
43-32	0.5	-1.651	2.651	1
44-32	0	-2.041	2.041	1
45-32	-0.5	-3.727	2.727	1
46-32	0.2	-1.841	2.241	1
48-32	0.4	-1.641	2.441	1
49-32	-0.5	-3.727	2.727	1
50-32	0.5	-1.512	2.512	1
51-32	-0.5	-3.727	2.727	1
52-32	0.417	-1.596	2.429	1
54-32	0.375	-1.708	2.458	1
55-32	0.167	-1.893	2.226	1
56-32	0.5	-1.612	2.612	1
57-32	0.1	-2.104	2.304	1
58-32	0.5	-1.905	2.905	1
59-32	0.357	-1.755	2.47	1
60-32	0.25	-2.032	2.532	1
62-32	0.5	-1.905	2.905	1
66-32	1.25	-1.032	3.532	0.943
36-34	0	-1.863	1.863	1
37-34	0.05	-1.717	1.817	1
39-34	0.05	-1.509	1.609	1
41-34	0.139	-1.444	1.722	1
42-34	0.25	-2.696	3.196	1
43-34	0.25	-1.451	1.951	1
44-34	-0.25	-1.809	1.309	1
45-34	-0.75	-3.696	2.196	1
46-34	-0.05	-1.609	1.509	1
48-34	0.15	-1.409	1.709	1
49-34	-0.75	-3.696	2.196	1
50-34	0.25	-1.271	1.771	1
51-34	-0.75	-3.696	2.196	1
52-34	0.167	-1.354	1.688	1
54-34	0.125	-1.488	1.738	1
55-34	-0.083	-1.667	1.5	1
56-34	0.25	-1.401	1.901	1
57-34	-0.15	-1.917	1.617	1
58-34	0.25	-1.762	2.262	1
59-34	0.107	-1.544	1.759	1
60-34	0	-1.863	1.863	1
62-34	0.25	-1.762	2.262	1
66-34	1	-0.863	2.863	0.954
37-36	0.05	-1.717	1.817	1
39-36	0.05	-1.509	1.609	1
41-36	0.139	-1.444	1.722	1
42-36	0.25	-2.696	3.196	1
43-36	0.25	-1.451	1.951	1
44-36	-0.25	-1.809	1.309	1
45-36	-0.75	-3.696	2.196	1
46-36	-0.05	-1.609	1.509	1
48-36	0.15	-1.409	1.709	1
49-36	-0.75	-3.696	2.196	1
50-36	0.25	-1.271	1.771	1
51-36	-0.75	-3.696	2.196	1
52-36	0.167	-1.354	1.688	1
54-36	0.125	-1.488	1.738	1
55-36	-0.083	-1.667	1.5	1
56-36	0.25	-1.401	1.901	1
57-36	-0.15	-1.917	1.617	1
58-36	0.25	-1.762	2.262	1
59-36	0.107	-1.544	1.759	1
60-36	0	-1.863	1.863	1
62-36	0.25	-1.762	2.262	1
66-36	1	-0.863	2.863	0.954
39-37	0	-1.443	1.443	1
41-37	0.089	-1.381	1.558	1
42-37	0.2	-2.686	3.086	1
43-37	0.2	-1.395	1.795	1
44-37	-0.3	-1.743	1.143	1
45-37	-0.8	-3.686	2.086	1
46-37	-0.1	-1.543	1.343	1
48-37	0.1	-1.343	1.543	1
49-37	-0.8	-3.686	2.086	1
50-37	0.2	-1.202	1.602	1
51-37	-0.8	-3.686	2.086	1
52-37	0.117	-1.286	1.519	1
54-37	0.075	-1.427	1.577	1
55-37	-0.133	-1.603	1.336	1
56-37	0.2	-1.343	1.743	1
57-37	-0.2	-1.866	1.466	1
58-37	0.2	-1.724	2.124	1
59-37	0.057	-1.486	1.6	1
60-37	-0.05	-1.817	1.717	1
62-37	0.2	-1.724	2.124	1
66-37	0.95	-0.817	2.717	0.953
41-39	0.089	-1.122	1.299	1
42-39	0.2	-2.563	2.963	1
43-39	0.2	-1.161	1.561	1
44-39	-0.3	-1.478	0.878	1
45-39	-0.8	-3.563	1.963	1
46-39	-0.1	-1.278	1.078	1
48-39	0.1	-1.078	1.278	1
49-39	-0.8	-3.563	1.963	1
50-39	0.2	-0.928	1.328	1
51-39	-0.8	-3.563	1.963	1
52-39	0.117	-1.011	1.245	1
54-39	0.075	-1.175	1.325	1
55-39	-0.133	-1.344	1.077	1
56-39	0.2	-1.098	1.498	1
57-39	-0.2	-1.643	1.243	1
58-39	0.2	-1.534	1.934	1
59-39	0.057	-1.241	1.356	1
60-39	-0.05	-1.609	1.509	1
62-39	0.2	-1.534	1.934	1
66-39	0.95	-0.609	2.509	0.848
42-41	0.111	-2.666	2.888	1
43-41	0.111	-1.277	1.5	1
44-41	-0.389	-1.599	0.822	1
45-41	-0.889	-3.666	1.888	1
46-41	-0.189	-1.399	1.022	1
48-41	0.011	-1.199	1.222	1
49-41	-0.889	-3.666	1.888	1
50-41	0.111	-1.051	1.273	1
51-41	-0.889	-3.666	1.888	1
52-41	0.028	-1.134	1.19	1
54-41	-0.014	-1.294	1.266	1
55-41	-0.222	-1.464	1.02	1
56-41	0.111	-1.217	1.439	1
57-41	-0.289	-1.758	1.181	1
58-41	0.111	-1.645	1.868	1
59-41	-0.032	-1.359	1.296	1
60-41	-0.139	-1.722	1.444	1
62-41	0.111	-1.645	1.868	1
66-41	0.861	-0.722	2.444	0.947
43-42	0	-2.846	2.846	1
44-42	-0.5	-3.263	2.263	1
45-42	-1	-4.726	2.726	1
46-42	-0.3	-3.063	2.463	1
48-42	-0.1	-2.863	2.663	1
49-42	-1	-4.726	2.726	1
50-42	0	-2.742	2.742	1
51-42	-1	-4.726	2.726	1
52-42	-0.083	-2.826	2.659	1
54-42	-0.125	-2.919	2.669	1
55-42	-0.333	-3.111	2.444	1
56-42	0	-2.817	2.817	1
57-42	-0.4	-3.286	2.486	1
58-42	0	-3.042	3.042	1
59-42	-0.143	-2.959	2.674	1
60-42	-0.25	-3.196	2.696	1
62-42	0	-3.042	3.042	1
66-42	0.75	-2.196	3.696	1
44-43	-0.5	-1.861	0.861	1
45-43	-1	-3.846	1.846	1
46-43	-0.3	-1.661	1.061	1
48-43	-0.1	-1.461	1.261	1
49-43	-1	-3.846	1.846	1
50-43	0	-1.317	1.317	1
51-43	-1	-3.846	1.846	1
52-43	-0.083	-1.401	1.234	1
54-43	-0.125	-1.548	1.298	1
55-43	-0.333	-1.722	1.055	1
56-43	0	-1.466	1.466	1
57-43	-0.4	-1.995	1.195	1
58-43	0	-1.863	1.863	1
59-43	-0.143	-1.609	1.323	1
60-43	-0.25	-1.951	1.451	1
62-43	0	-1.863	1.863	1
66-43	0.75	-0.951	2.451	0.996
45-44	-0.5	-3.263	2.263	1
46-44	0.2	-0.978	1.378	1
48-44	0.4	-0.778	1.578	1
49-44	-0.5	-3.263	2.263	1
50-44	0.5	-0.628	1.628	0.996
51-44	-0.5	-3.263	2.263	1
52-44	0.417	-0.711	1.545	1
54-44	0.375	-0.875	1.625	1
55-44	0.167	-1.044	1.377	1
56-44	0.5	-0.798	1.798	1
57-44	0.1	-1.343	1.543	1
58-44	0.5	-1.234	2.234	1
59-44	0.357	-0.941	1.656	1
60-44	0.25	-1.309	1.809	1
62-44	0.5	-1.234	2.234	1
66-44	1.25	-0.309	2.809	0.334
46-45	0.7	-2.063	3.463	1
48-45	0.9	-1.863	3.663	1
49-45	0	-3.726	3.726	1
50-45	1	-1.742	3.742	1
51-45	0	-3.726	3.726	1
52-45	0.917	-1.826	3.659	1
54-45	0.875	-1.919	3.669	1
55-45	0.667	-2.111	3.444	1
56-45	1	-1.817	3.817	1
57-45	0.6	-2.286	3.486	1
58-45	1	-2.042	4.042	1
59-45	0.857	-1.959	3.674	1
60-45	0.75	-2.196	3.696	1
62-45	1	-2.042	4.042	1
66-45	1.75	-1.196	4.696	0.877
48-46	0.2	-0.978	1.378	1
49-46	-0.7	-3.463	2.063	1
50-46	0.3	-0.828	1.428	1
51-46	-0.7	-3.463	2.063	1
52-46	0.217	-0.911	1.345	1
54-46	0.175	-1.075	1.425	1
55-46	-0.033	-1.244	1.177	1
56-46	0.3	-0.998	1.598	1
57-46	-0.1	-1.543	1.343	1
58-46	0.3	-1.434	2.034	1
59-46	0.157	-1.141	1.456	1
60-46	0.05	-1.509	1.609	1
62-46	0.3	-1.434	2.034	1
66-46	1.05	-0.509	2.609	0.693
49-48	-0.9	-3.663	1.863	1
50-48	0.1	-1.028	1.228	1
51-48	-0.9	-3.663	1.863	1
52-48	0.017	-1.111	1.145	1
54-48	-0.025	-1.275	1.225	1
55-48	-0.233	-1.444	0.977	1
56-48	0.1	-1.198	1.398	1
57-48	-0.3	-1.743	1.143	1
58-48	0.1	-1.634	1.834	1
59-48	-0.043	-1.341	1.256	1
60-48	-0.15	-1.709	1.409	1
62-48	0.1	-1.634	1.834	1
66-48	0.85	-0.709	2.409	0.945
50-49	1	-1.742	3.742	1
51-49	0	-3.726	3.726	1
52-49	0.917	-1.826	3.659	1
54-49	0.875	-1.919	3.669	1
55-49	0.667	-2.111	3.444	1
56-49	1	-1.817	3.817	1
57-49	0.6	-2.286	3.486	1
58-49	1	-2.042	4.042	1
59-49	0.857	-1.959	3.674	1
60-49	0.75	-2.196	3.696	1
62-49	1	-2.042	4.042	1
66-49	1.75	-1.196	4.696	0.877
51-50	-1	-3.742	1.742	1
52-50	-0.083	-1.159	0.992	1
54-50	-0.125	-1.328	1.078	1
55-50	-0.333	-1.495	0.828	1
56-50	0	-1.253	1.253	1
57-50	-0.4	-1.802	1.002	1
58-50	0	-1.701	1.701	1
59-50	-0.143	-1.396	1.11	1
60-50	-0.25	-1.771	1.271	1
62-50	0	-1.701	1.701	1
66-50	0.75	-0.771	2.271	0.982
52-51	0.917	-1.826	3.659	1
54-51	0.875	-1.919	3.669	1
55-51	0.667	-2.111	3.444	1
56-51	1	-1.817	3.817	1
57-51	0.6	-2.286	3.486	1
58-51	1	-2.042	4.042	1
59-51	0.857	-1.959	3.674	1
60-51	0.75	-2.196	3.696	1
62-51	1	-2.042	4.042	1
66-51	1.75	-1.196	4.696	0.877
54-52	-0.042	-1.244	1.161	1
55-52	-0.25	-1.412	0.912	1
56-52	0.083	-1.17	1.336	1
57-52	-0.317	-1.719	1.086	1
58-52	0.083	-1.617	1.784	1
59-52	-0.06	-1.313	1.194	1
60-52	-0.167	-1.688	1.354	1
62-52	0.083	-1.617	1.784	1
66-52	0.833	-0.688	2.354	0.943
55-54	-0.208	-1.489	1.072	1
56-54	0.125	-1.239	1.489	1
57-54	-0.275	-1.777	1.227	1
58-54	0.125	-1.659	1.909	1
59-54	-0.018	-1.381	1.346	1
60-54	-0.125	-1.738	1.488	1
62-54	0.125	-1.659	1.909	1
66-54	0.875	-0.738	2.488	0.948
56-55	0.333	-0.994	1.661	1
57-55	-0.067	-1.536	1.403	1
58-55	0.333	-1.423	2.09	1
59-55	0.19	-1.137	1.518	1
60-55	0.083	-1.5	1.667	1
62-55	0.333	-1.423	2.09	1
66-55	1.083	-0.5	2.667	0.664
57-56	-0.4	-1.943	1.143	1
58-56	0	-1.818	1.818	1
59-56	-0.143	-1.551	1.265	1
60-56	-0.25	-1.901	1.401	1
62-56	0	-1.818	1.818	1
66-56	0.75	-0.901	2.401	0.994
58-57	0.4	-1.524	2.324	1
59-57	0.257	-1.286	1.8	1
60-57	0.15	-1.617	1.917	1
62-57	0.4	-1.524	2.324	1
66-57	1.15	-0.617	2.917	0.754
59-58	-0.143	-1.961	1.675	1
60-58	-0.25	-2.262	1.762	1
62-58	0	-2.151	2.151	1
66-58	0.75	-1.262	2.762	1
60-59	-0.107	-1.759	1.544	1
62-59	0.143	-1.675	1.961	1
66-59	0.893	-0.759	2.544	0.95
62-60	0.25	-1.762	2.262	1
66-60	1	-0.863	2.863	0.954
66-62	0.75	-1.262	2.762	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	26	0.63	0.914
	126

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2/30git1290774079.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2/30git1290774079.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2/4bpzw1290774079.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/26/t1290774030z4qzxf1z4aahzg2/4bpzw1290774079.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = 2 ; par3 = TRUE ;

Parameters (R input):

par1 = 1 ; par2 = 2 ; par3 = TRUE ;

R code (references can be found in the software module):

cat1 <- as.numeric(par1) #

cat2<- as.numeric(par2) #

intercept<-as.logical(par3)

x <- t(x)

x1<-as.numeric(x[,cat1])

f1<-as.character(x[,cat2])

xdf<-data.frame(x1,f1)

(V1<-dimnames(y)[[1]][cat1])

(V2<-dimnames(y)[[1]][cat2])

names(xdf)<-c('Response', 'Treatment')

if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )

(aov.xdf<-aov(lmxdf) )

(anova.xdf<-anova(lmxdf) )

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, 'means',,TRUE)

for(i in 1:length(lmxdf$coefficients)){

a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)

}

a<-table.row.end(a)

a<-table.end(a)

table.save(a,file='mytable.tab')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, ' ',,TRUE)

a<-table.element(a, 'Df',,FALSE)

a<-table.element(a, 'Sum Sq',,FALSE)

a<-table.element(a, 'Mean Sq',,FALSE)

a<-table.element(a, 'F value',,FALSE)

a<-table.element(a, 'Pr(>F)',,FALSE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, V2,,TRUE)

a<-table.element(a, anova.xdf$Df[1],,FALSE)

a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)

a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)

a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)

a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, 'Residuals',,TRUE)

a<-table.element(a, anova.xdf$Df[2],,FALSE)

a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)

a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)

a<-table.element(a, ' ',,FALSE)

a<-table.element(a, ' ',,FALSE)

a<-table.row.end(a)

a<-table.end(a)

table.save(a,file='mytable1.tab')

bitmap(file='anovaplot.png')

boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)

dev.off()

if(intercept==TRUE){

thsd<-TukeyHSD(aov.xdf)

bitmap(file='TukeyHSDPlot.png')

plot(thsd)

dev.off()

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a, ' ', 1, TRUE)

for(i in 1:4){

a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)

}

a<-table.row.end(a)

for(i in 1:length(rownames(thsd[[1]]))){

a<-table.row.start(a)

a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)

for(j in 1:4){

a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)

}

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable2.tab')

}

if(intercept==FALSE){

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'TukeyHSD Message', 1,TRUE)

a<-table.row.end(a)

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)

a<-table.row.end(a)

a<-table.end(a)

table.save(a,file='mytable2.tab')

}

library(car)

lt.lmxdf<-levene.test(lmxdf)

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,' ', 1, TRUE)

for (i in 1:3){

a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)

}

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'Group', 1, TRUE)

for (i in 1:3){

a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)

}

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,' ', 1, TRUE)

a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)

a<-table.element(a,' ', 1, FALSE)

a<-table.element(a,' ', 1, FALSE)

a<-table.row.end(a)

a<-table.end(a)

table.save(a,file='mytable3.tab')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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