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COMPENDIUM 8

*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: Sun, 28 Nov 2010 22:59:55 +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/29/t1290985238xabuirduuazrg36.htm/, Retrieved Mon, 29 Nov 2010 00:00:41 +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/29/t1290985238xabuirduuazrg36.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:

Mother's verbal IQ compared to 30 month child ability

Dataseries X:

» Textbox « » Textfile « » CSV «

1 36 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 1 48 2 41 3 50 2 50 2 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 3 37 2 41 2 30 3 52 1 30 1 41 2 44 2 66 1 48 3 43 1 57 1 46 1 54 2 48 2 48 2 52 1 62 1 58 2 58 2 62 2 48 2 46 2 34 3 66 2 52 1 55 1 55 2 57 2 56 2 55 3 56 2 54 2 55 3 46 1 52 2 32 1 44 2 46 2 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 3 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 48 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 2 39 1 56 1 59 1 46 2 57 2 50 2 54 2 50 3 60 3 59 3 41 2 48 2 59 2 60 1 56 2 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
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

ANOVA Model
MVRBIQ0 ~ MC30VRB
means	1.5	-0.5	0	0.5	0.1	0.5	0.4	0.3	0.5	0.5	0.1	-0.5	0.2	0.423	-0.5	0.667	-0.5	0.5	0.5	0.167	0.5	0.1	0.5	0.5	0.25	0.5	1.25

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
MC30VRB	26	11.254	0.433	0.914	0.589
Residuals	133	62.99	0.474

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
31-30	-0.5	-3.407	2.407	1
32-30	0	-2.252	2.252	1
34-30	0.5	-1.338	2.338	1
36-30	0.1	-1.644	1.844	1
37-30	0.5	-1.244	2.244	1
39-30	0.4	-1.138	1.938	1
41-30	0.3	-1.238	1.838	1
42-30	0.5	-2.407	3.407	1
43-30	0.5	-1.178	2.178	1
44-30	0.1	-1.438	1.638	1
45-30	-0.5	-3.407	2.407	1
46-30	0.2	-1.338	1.738	1
48-30	0.423	-1.063	1.91	1
49-30	-0.5	-3.407	2.407	1
50-30	0.667	-0.834	2.168	0.996
51-30	-0.5	-3.407	2.407	1
52-30	0.5	-0.987	1.987	1
54-30	0.5	-1.092	2.092	1
55-30	0.167	-1.396	1.729	1
56-30	0.5	-1.092	2.092	1
57-30	0.1	-1.644	1.844	1
58-30	0.5	-1.486	2.486	1
59-30	0.5	-1.13	2.13	1
60-30	0.25	-1.588	2.088	1
62-30	0.5	-1.486	2.486	1
66-30	1.25	-0.588	3.088	0.678
32-31	0.5	-2.684	3.684	1
34-31	1	-1.907	3.907	1
36-31	0.6	-2.248	3.448	1
37-31	1	-1.848	3.848	1
39-31	0.9	-1.827	3.627	1
41-31	0.8	-1.927	3.527	1
42-31	1	-2.677	4.677	1
43-31	1	-1.808	3.808	1
44-31	0.6	-2.127	3.327	1
45-31	0	-3.677	3.677	1
46-31	0.7	-2.027	3.427	1
48-31	0.923	-1.775	3.621	1
49-31	0	-3.677	3.677	1
50-31	1.167	-1.539	3.873	0.997
51-31	0	-3.677	3.677	1
52-31	1	-1.698	3.698	1
54-31	1	-1.758	3.758	1
55-31	0.667	-2.074	3.407	1
56-31	1	-1.758	3.758	1
57-31	0.6	-2.248	3.448	1
58-31	1	-2.002	4.002	1
59-31	1	-1.779	3.779	1
60-31	0.75	-2.157	3.657	1
62-31	1	-2.002	4.002	1
66-31	1.75	-1.157	4.657	0.865
34-32	0.5	-1.752	2.752	1
36-32	0.1	-2.075	2.275	1
37-32	0.5	-1.675	2.675	1
39-32	0.4	-1.614	2.414	1
41-32	0.3	-1.714	2.314	1
42-32	0.5	-2.684	3.684	1
43-32	0.5	-1.623	2.623	1
44-32	0.1	-1.914	2.114	1
45-32	-0.5	-3.684	2.684	1
46-32	0.2	-1.814	2.214	1
48-32	0.423	-1.552	2.398	1
49-32	-0.5	-3.684	2.684	1
50-32	0.667	-1.319	2.652	1
51-32	-0.5	-3.684	2.684	1
52-32	0.5	-1.475	2.475	1
54-32	0.5	-1.555	2.555	1
55-32	0.167	-1.866	2.199	1
56-32	0.5	-1.555	2.555	1
57-32	0.1	-2.075	2.275	1
58-32	0.5	-1.873	2.873	1
59-32	0.5	-1.584	2.584	1
60-32	0.25	-2.002	2.502	1
62-32	0.5	-1.873	2.873	1
66-32	1.25	-1.002	3.502	0.936
36-34	-0.4	-2.144	1.344	1
37-34	0	-1.744	1.744	1
39-34	-0.1	-1.638	1.438	1
41-34	-0.2	-1.738	1.338	1
42-34	0	-2.907	2.907	1
43-34	0	-1.678	1.678	1
44-34	-0.4	-1.938	1.138	1
45-34	-1	-3.907	1.907	1
46-34	-0.3	-1.838	1.238	1
48-34	-0.077	-1.563	1.41	1
49-34	-1	-3.907	1.907	1
50-34	0.167	-1.334	1.668	1
51-34	-1	-3.907	1.907	1
52-34	0	-1.487	1.487	1
54-34	0	-1.592	1.592	1
55-34	-0.333	-1.896	1.229	1
56-34	0	-1.592	1.592	1
57-34	-0.4	-2.144	1.344	1
58-34	0	-1.986	1.986	1
59-34	0	-1.63	1.63	1
60-34	-0.25	-2.088	1.588	1
62-34	0	-1.986	1.986	1
66-34	0.75	-1.088	2.588	0.999
37-36	0.4	-1.244	2.044	1
39-36	0.3	-1.124	1.724	1
41-36	0.2	-1.224	1.624	1
42-36	0.4	-2.448	3.248	1
43-36	0.4	-1.174	1.974	1
44-36	0	-1.424	1.424	1
45-36	-0.6	-3.448	2.248	1
46-36	0.1	-1.324	1.524	1
48-36	0.323	-1.045	1.691	1
49-36	-0.6	-3.448	2.248	1
50-36	0.567	-0.817	1.951	0.999
51-36	-0.6	-3.448	2.248	1
52-36	0.4	-0.968	1.768	1
54-36	0.4	-1.082	1.882	1
55-36	0.067	-1.383	1.517	1
56-36	0.4	-1.082	1.882	1
57-36	0	-1.644	1.644	1
58-36	0.4	-1.499	2.299	1
59-36	0.4	-1.122	1.922	1
60-36	0.15	-1.594	1.894	1
62-36	0.4	-1.499	2.299	1
66-36	1.15	-0.594	2.894	0.734
39-37	-0.1	-1.524	1.324	1
41-37	-0.2	-1.624	1.224	1
42-37	0	-2.848	2.848	1
43-37	0	-1.574	1.574	1
44-37	-0.4	-1.824	1.024	1
45-37	-1	-3.848	1.848	1
46-37	-0.3	-1.724	1.124	1
48-37	-0.077	-1.445	1.291	1
49-37	-1	-3.848	1.848	1
50-37	0.167	-1.217	1.551	1
51-37	-1	-3.848	1.848	1
52-37	0	-1.368	1.368	1
54-37	0	-1.482	1.482	1
55-37	-0.333	-1.783	1.117	1
56-37	0	-1.482	1.482	1
57-37	-0.4	-2.044	1.244	1
58-37	0	-1.899	1.899	1
59-37	0	-1.522	1.522	1
60-37	-0.25	-1.994	1.494	1
62-37	0	-1.899	1.899	1
66-37	0.75	-0.994	2.494	0.997
41-39	-0.1	-1.263	1.063	1
42-39	0.1	-2.627	2.827	1
43-39	0.1	-1.243	1.443	1
44-39	-0.3	-1.463	0.863	1
45-39	-0.9	-3.627	1.827	1
46-39	-0.2	-1.363	0.963	1
48-39	0.023	-1.07	1.117	1
49-39	-0.9	-3.627	1.827	1
50-39	0.267	-0.847	1.38	1
51-39	-0.9	-3.627	1.827	1
52-39	0.1	-0.994	1.194	1
54-39	0.1	-1.133	1.333	1
55-39	-0.233	-1.428	0.961	1
56-39	0.1	-1.133	1.333	1
57-39	-0.3	-1.724	1.124	1
58-39	0.1	-1.611	1.811	1
59-39	0.1	-1.181	1.381	1
60-39	-0.15	-1.688	1.388	1
62-39	0.1	-1.611	1.811	1
66-39	0.85	-0.688	2.388	0.939
42-41	0.2	-2.527	2.927	1
43-41	0.2	-1.143	1.543	1
44-41	-0.2	-1.363	0.963	1
45-41	-0.8	-3.527	1.927	1
46-41	-0.1	-1.263	1.063	1
48-41	0.123	-0.97	1.217	1
49-41	-0.8	-3.527	1.927	1
50-41	0.367	-0.747	1.48	1
51-41	-0.8	-3.527	1.927	1
52-41	0.2	-0.894	1.294	1
54-41	0.2	-1.033	1.433	1
55-41	-0.133	-1.328	1.061	1
56-41	0.2	-1.033	1.433	1
57-41	-0.2	-1.624	1.224	1
58-41	0.2	-1.511	1.911	1
59-41	0.2	-1.081	1.481	1
60-41	-0.05	-1.588	1.488	1
62-41	0.2	-1.511	1.911	1
66-41	0.95	-0.588	2.488	0.834
43-42	0	-2.808	2.808	1
44-42	-0.4	-3.127	2.327	1
45-42	-1	-4.677	2.677	1
46-42	-0.3	-3.027	2.427	1
48-42	-0.077	-2.775	2.621	1
49-42	-1	-4.677	2.677	1
50-42	0.167	-2.539	2.873	1
51-42	-1	-4.677	2.677	1
52-42	0	-2.698	2.698	1
54-42	0	-2.758	2.758	1
55-42	-0.333	-3.074	2.407	1
56-42	0	-2.758	2.758	1
57-42	-0.4	-3.248	2.448	1
58-42	0	-3.002	3.002	1
59-42	0	-2.779	2.779	1
60-42	-0.25	-3.157	2.657	1
62-42	0	-3.002	3.002	1
66-42	0.75	-2.157	3.657	1
44-43	-0.4	-1.743	0.943	1
45-43	-1	-3.808	1.808	1
46-43	-0.3	-1.643	1.043	1
48-43	-0.077	-1.36	1.206	1
49-43	-1	-3.808	1.808	1
50-43	0.167	-1.133	1.467	1
51-43	-1	-3.808	1.808	1
52-43	0	-1.283	1.283	1
54-43	0	-1.404	1.404	1
55-43	-0.333	-1.704	1.037	1
56-43	0	-1.404	1.404	1
57-43	-0.4	-1.974	1.174	1
58-43	0	-1.838	1.838	1
59-43	0	-1.446	1.446	1
60-43	-0.25	-1.928	1.428	1
62-43	0	-1.838	1.838	1
66-43	0.75	-0.928	2.428	0.995
45-44	-0.6	-3.327	2.127	1
46-44	0.1	-1.063	1.263	1
48-44	0.323	-0.77	1.417	1
49-44	-0.6	-3.327	2.127	1
50-44	0.567	-0.547	1.68	0.975
51-44	-0.6	-3.327	2.127	1
52-44	0.4	-0.694	1.494	1
54-44	0.4	-0.833	1.633	1
55-44	0.067	-1.128	1.261	1
56-44	0.4	-0.833	1.633	1
57-44	0	-1.424	1.424	1
58-44	0.4	-1.311	2.111	1
59-44	0.4	-0.881	1.681	1
60-44	0.15	-1.388	1.688	1
62-44	0.4	-1.311	2.111	1
66-44	1.15	-0.388	2.688	0.482
46-45	0.7	-2.027	3.427	1
48-45	0.923	-1.775	3.621	1
49-45	0	-3.677	3.677	1
50-45	1.167	-1.539	3.873	0.997
51-45	0	-3.677	3.677	1
52-45	1	-1.698	3.698	1
54-45	1	-1.758	3.758	1
55-45	0.667	-2.074	3.407	1
56-45	1	-1.758	3.758	1
57-45	0.6	-2.248	3.448	1
58-45	1	-2.002	4.002	1
59-45	1	-1.779	3.779	1
60-45	0.75	-2.157	3.657	1
62-45	1	-2.002	4.002	1
66-45	1.75	-1.157	4.657	0.865
48-46	0.223	-0.87	1.317	1
49-46	-0.7	-3.427	2.027	1
50-46	0.467	-0.647	1.58	0.998
51-46	-0.7	-3.427	2.027	1
52-46	0.3	-0.794	1.394	1
54-46	0.3	-0.933	1.533	1
55-46	-0.033	-1.228	1.161	1
56-46	0.3	-0.933	1.533	1
57-46	-0.1	-1.524	1.324	1
58-46	0.3	-1.411	2.011	1
59-46	0.3	-0.981	1.581	1
60-46	0.05	-1.488	1.588	1
62-46	0.3	-1.411	2.011	1
66-46	1.05	-0.488	2.588	0.671
49-48	-0.923	-3.621	1.775	1
50-48	0.244	-0.797	1.284	1
51-48	-0.923	-3.621	1.775	1
52-48	0.077	-0.943	1.097	1
54-48	0.077	-1.091	1.245	1
55-48	-0.256	-1.384	0.871	1
56-48	0.077	-1.091	1.245	1
57-48	-0.323	-1.691	1.045	1
58-48	0.077	-1.588	1.742	1
59-48	0.077	-1.142	1.296	1
60-48	-0.173	-1.66	1.313	1
62-48	0.077	-1.588	1.742	1
66-48	0.827	-0.66	2.313	0.934
50-49	1.167	-1.539	3.873	0.997
51-49	0	-3.677	3.677	1
52-49	1	-1.698	3.698	1
54-49	1	-1.758	3.758	1
55-49	0.667	-2.074	3.407	1
56-49	1	-1.758	3.758	1
57-49	0.6	-2.248	3.448	1
58-49	1	-2.002	4.002	1
59-49	1	-1.779	3.779	1
60-49	0.75	-2.157	3.657	1
62-49	1	-2.002	4.002	1
66-49	1.75	-1.157	4.657	0.865
51-50	-1.167	-3.873	1.539	0.997
52-50	-0.167	-1.207	0.874	1
54-50	-0.167	-1.353	1.02	1
55-50	-0.5	-1.646	0.646	0.997
56-50	-0.167	-1.353	1.02	1
57-50	-0.567	-1.951	0.817	0.999
58-50	-0.167	-1.845	1.512	1
59-50	-0.167	-1.403	1.07	1
60-50	-0.417	-1.918	1.084	1
62-50	-0.167	-1.845	1.512	1
66-50	0.583	-0.918	2.084	0.999
52-51	1	-1.698	3.698	1
54-51	1	-1.758	3.758	1
55-51	0.667	-2.074	3.407	1
56-51	1	-1.758	3.758	1
57-51	0.6	-2.248	3.448	1
58-51	1	-2.002	4.002	1
59-51	1	-1.779	3.779	1
60-51	0.75	-2.157	3.657	1
62-51	1	-2.002	4.002	1
66-51	1.75	-1.157	4.657	0.865
54-52	0	-1.168	1.168	1
55-52	-0.333	-1.461	0.794	1
56-52	0	-1.168	1.168	1
57-52	-0.4	-1.768	0.968	1
58-52	0	-1.665	1.665	1
59-52	0	-1.219	1.219	1
60-52	-0.25	-1.737	1.237	1
62-52	0	-1.665	1.665	1
66-52	0.75	-0.737	2.237	0.977
55-54	-0.333	-1.597	0.93	1
56-54	0	-1.3	1.3	1
57-54	-0.4	-1.882	1.082	1
58-54	0	-1.76	1.76	1
59-54	0	-1.346	1.346	1
60-54	-0.25	-1.842	1.342	1
62-54	0	-1.76	1.76	1
66-54	0.75	-0.842	2.342	0.99
56-55	0.333	-0.93	1.597	1
57-55	-0.067	-1.517	1.383	1
58-55	0.333	-1.4	2.067	1
59-55	0.333	-0.977	1.644	1
60-55	0.083	-1.479	1.646	1
62-55	0.333	-1.4	2.067	1
66-55	1.083	-0.479	2.646	0.64
57-56	-0.4	-1.882	1.082	1
58-56	0	-1.76	1.76	1
59-56	0	-1.346	1.346	1
60-56	-0.25	-1.842	1.342	1
62-56	0	-1.76	1.76	1
66-56	0.75	-0.842	2.342	0.99
58-57	0.4	-1.499	2.299	1
59-57	0.4	-1.122	1.922	1
60-57	0.15	-1.594	1.894	1
62-57	0.4	-1.499	2.299	1
66-57	1.15	-0.594	2.894	0.734
59-58	0	-1.794	1.794	1
60-58	-0.25	-2.236	1.736	1
62-58	0	-2.123	2.123	1
66-58	0.75	-1.236	2.736	1
60-59	-0.25	-1.88	1.38	1
62-59	0	-1.794	1.794	1
66-59	0.75	-0.88	2.38	0.993
62-60	0.25	-1.736	2.236	1
66-60	1	-0.838	2.838	0.948
66-62	0.75	-1.236	2.736	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	26	0.62	0.922
	133

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/29/t1290985238xabuirduuazrg36/3yd6i1290985188.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/29/t1290985238xabuirduuazrg36/3yd6i1290985188.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/29/t1290985238xabuirduuazrg36/494521290985188.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Nov/29/t1290985238xabuirduuazrg36/494521290985188.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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