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week9 ex3

*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: Chi Square Measure of Association- Free Statistics Software (Calculator)

Date of computation: Sat, 12 Dec 2009 12:03:23 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/12/t12606446406qqy3agwmimgi76.htm/, Retrieved Sat, 12 Dec 2009 20:04:03 +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/2009/Dec/12/t12606446406qqy3agwmimgi76.htm/},
    year = {2009},
}
@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 = {2009},
    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 «

1 36 1 36 2 56 2 48 2 32 1 44 2 39 2 34 3 41 3 50 1 39 3 62 2 52 3 37 2 50 1 41 2 55 2 41 3 56 2 39 1 52 2 46 2 44 2 48 2 41 3 50 2 50 2 44 1 52 2 54 2 44 3 52 2 37 3 52 3 50 1 36 1 50 3 52 3 55 2 31 1 36 1 49 1 42 2 37 2 41 1 30 1 52 3 30 2 41 1 44 2 66 3 48 2 43 2 57 1 46 3 54 3 48 2 48 1 52 1 62 3 58 2 58 2 62 2 48 2 46 1 34 2 66 3 52 2 55 1 55 3 57 1 56 2 55 3 56 1 54 3 55 2 46 1 52 2 32 1 44 2 46 2 59 3 46 3 46 3 54 3 66 2 56 2 59 2 57 3 52 1 48 1 44 2 41 1 50 3 48 2 48 2 59 2 46 2 54 2 55 3 54 2 59 2 44 3 54 3 52 3 66 2 44 2 57 1 39 3 60 2 45 2 41 2 50 2 39 2 43 1 48 2 37 2 58 1 46 1 43 2 44 3 34 1 30 3 50 1 39 2 37 2 55 3 48 1 39 3 36 2 43 3 50 2 55 2 43 3 60 2 48 3 30 2 43 1 39 2 52 1 39 1 39 1 56 1 59 2 46 2 57 2 50 1 54 3 50 3 60 3 59 2 41 1 48 2 59 3 60 2 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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
MWARM30 ~ MC40VRB
means	2	0	0	0	-0.6	0.2	-0.7	0	-1	-0.167	-0.4	0	0	0.077	-1	0.333	-1	0.077	0.25	0.111	0	0.2	0.333	0	1	0	0.5

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
MC40VRB	26	19.298	0.742	1.503	0.072
Residuals	131	64.702	0.494

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
31-30	0	-2.969	2.969	1
32-30	0	-2.3	2.3	1
34-30	0	-2.028	2.028	1
36-30	-0.6	-2.382	1.182	1
37-30	0.2	-1.582	1.982	1
39-30	-0.7	-2.271	0.871	0.995
41-30	0	-1.596	1.596	1
42-30	-1	-3.969	1.969	1
43-30	-0.167	-1.881	1.548	1
44-30	-0.4	-1.971	1.171	1
45-30	0	-2.969	2.969	1
46-30	0	-1.571	1.571	1
48-30	0.077	-1.442	1.595	1
49-30	-1	-3.969	1.969	1
50-30	0.333	-1.2	1.867	1
51-30	-1	-3.969	1.969	1
52-30	0.077	-1.442	1.595	1
54-30	0.25	-1.376	1.876	1
55-30	0.111	-1.485	1.707	1
56-30	0	-1.626	1.626	1
57-30	0.2	-1.582	1.982	1
58-30	0.333	-1.695	2.362	1
59-30	0	-1.665	1.665	1
60-30	1	-0.878	2.878	0.958
62-30	0	-2.028	2.028	1
66-30	0.5	-1.378	2.378	1
32-31	0	-3.253	3.253	1
34-31	0	-3.067	3.067	1
36-31	-0.6	-3.509	2.309	1
37-31	0.2	-2.709	3.109	1
39-31	-0.7	-3.485	2.085	1
41-31	0	-2.799	2.799	1
42-31	-1	-4.756	2.756	1
43-31	-0.167	-3.035	2.702	1
44-31	-0.4	-3.185	2.385	1
45-31	0	-3.756	3.756	1
46-31	0	-2.785	2.785	1
48-31	0.077	-2.679	2.833	1
49-31	-1	-4.756	2.756	1
50-31	0.333	-2.431	3.098	1
51-31	-1	-4.756	2.756	1
52-31	0.077	-2.679	2.833	1
54-31	0.25	-2.567	3.067	1
55-31	0.111	-2.688	2.911	1
56-31	0	-2.817	2.817	1
57-31	0.2	-2.709	3.109	1
58-31	0.333	-2.733	3.4	1
59-31	0	-2.839	2.839	1
60-31	1	-1.969	3.969	1
62-31	0	-3.067	3.067	1
66-31	0.5	-2.469	3.469	1
34-32	0	-2.424	2.424	1
36-32	-0.6	-2.822	1.622	1
37-32	0.2	-2.022	2.422	1
39-32	-0.7	-2.757	1.357	1
41-32	0	-2.076	2.076	1
42-32	-1	-4.253	2.253	1
43-32	-0.167	-2.335	2.002	1
44-32	-0.4	-2.457	1.657	1
45-32	0	-3.253	3.253	1
46-32	0	-2.057	2.057	1
48-32	0.077	-1.94	2.094	1
49-32	-1	-4.253	2.253	1
50-32	0.333	-1.695	2.362	1
51-32	-1	-4.253	2.253	1
52-32	0.077	-1.94	2.094	1
54-32	0.25	-1.85	2.35	1
55-32	0.111	-1.965	2.187	1
56-32	0	-2.1	2.1	1
57-32	0.2	-2.022	2.422	1
58-32	0.333	-2.091	2.758	1
59-32	0	-2.129	2.129	1
60-32	1	-1.3	3.3	0.997
62-32	0	-2.424	2.424	1
66-32	0.5	-1.8	2.8	1
36-34	-0.6	-2.54	1.34	1
37-34	0.2	-1.74	2.14	1
39-34	-0.7	-2.448	1.048	0.999
41-34	0	-1.771	1.771	1
42-34	-1	-4.067	2.067	1
43-34	-0.167	-2.045	1.711	1
44-34	-0.4	-2.148	1.348	1
45-34	0	-3.067	3.067	1
46-34	0	-1.748	1.748	1
48-34	0.077	-1.624	1.778	1
49-34	-1	-4.067	2.067	1
50-34	0.333	-1.381	2.048	1
51-34	-1	-4.067	2.067	1
52-34	0.077	-1.624	1.778	1
54-34	0.25	-1.548	2.048	1
55-34	0.111	-1.659	1.882	1
56-34	0	-1.798	1.798	1
57-34	0.2	-1.74	2.14	1
58-34	0.333	-1.835	2.502	1
59-34	0	-1.833	1.833	1
60-34	1	-1.028	3.028	0.983
62-34	0	-2.168	2.168	1
66-34	0.5	-1.528	2.528	1
37-36	0.8	-0.88	2.48	0.989
39-36	-0.1	-1.555	1.355	1
41-36	0.6	-0.881	2.081	0.999
42-36	-0.4	-3.309	2.509	1
43-36	0.433	-1.175	2.042	1
44-36	0.2	-1.255	1.655	1
45-36	0.6	-2.309	3.509	1
46-36	0.6	-0.855	2.055	0.999
48-36	0.677	-0.721	2.075	0.986
49-36	-0.4	-3.309	2.509	1
50-36	0.933	-0.48	2.347	0.731
51-36	-0.4	-3.309	2.509	1
52-36	0.677	-0.721	2.075	0.986
54-36	0.85	-0.664	2.364	0.928
55-36	0.711	-0.77	2.192	0.988
56-36	0.6	-0.914	2.114	0.999
57-36	0.8	-0.88	2.48	0.989
58-36	0.933	-1.006	2.873	0.987
59-36	0.6	-0.955	2.155	1
60-36	1.6	-0.182	3.382	0.148
62-36	0.6	-1.34	2.54	1
66-36	1.1	-0.682	2.882	0.834
39-37	-0.9	-2.355	0.555	0.831
41-37	-0.2	-1.681	1.281	1
42-37	-1.2	-4.109	1.709	0.999
43-37	-0.367	-1.975	1.242	1
44-37	-0.6	-2.055	0.855	0.999
45-37	-0.2	-3.109	2.709	1
46-37	-0.2	-1.655	1.255	1
48-37	-0.123	-1.521	1.275	1
49-37	-1.2	-4.109	1.709	0.999
50-37	0.133	-1.28	1.547	1
51-37	-1.2	-4.109	1.709	0.999
52-37	-0.123	-1.521	1.275	1
54-37	0.05	-1.464	1.564	1
55-37	-0.089	-1.57	1.392	1
56-37	-0.2	-1.714	1.314	1
57-37	0	-1.68	1.68	1
58-37	0.133	-1.806	2.073	1
59-37	-0.2	-1.755	1.355	1
60-37	0.8	-0.982	2.582	0.995
62-37	-0.2	-2.14	1.74	1
66-37	0.3	-1.482	2.082	1
41-39	0.7	-0.52	1.92	0.911
42-39	-0.3	-3.085	2.485	1
43-39	0.533	-0.838	1.905	0.999
44-39	0.3	-0.888	1.488	1
45-39	0.7	-2.085	3.485	1
46-39	0.7	-0.488	1.888	0.887
48-39	0.777	-0.34	1.894	0.633
49-39	-0.3	-3.085	2.485	1
50-39	1.033	-0.104	2.17	0.133
51-39	-0.3	-3.085	2.485	1
52-39	0.777	-0.34	1.894	0.633
54-39	0.95	-0.31	2.21	0.463
55-39	0.811	-0.409	2.031	0.719
56-39	0.7	-0.56	1.96	0.935
57-39	0.9	-0.555	2.355	0.831
58-39	1.033	-0.715	2.782	0.884
59-39	0.7	-0.609	2.009	0.956
60-39	1.7	0.129	3.271	0.018
62-39	0.7	-1.048	2.448	0.999
66-39	1.2	-0.371	2.771	0.436
42-41	-1	-3.799	1.799	1
43-41	-0.167	-1.566	1.233	1
44-41	-0.4	-1.62	0.82	1
45-41	0	-2.799	2.799	1
46-41	0	-1.22	1.22	1
48-41	0.077	-1.075	1.229	1
49-41	-1	-3.799	1.799	1
50-41	0.333	-0.838	1.504	1
51-41	-1	-3.799	1.799	1
52-41	0.077	-1.075	1.229	1
54-41	0.25	-1.041	1.541	1
55-41	0.111	-1.141	1.363	1
56-41	0	-1.291	1.291	1
57-41	0.2	-1.281	1.681	1
58-41	0.333	-1.437	2.104	1
59-41	0	-1.338	1.338	1
60-41	1	-0.596	2.596	0.814
62-41	0	-1.771	1.771	1
66-41	0.5	-1.096	2.096	1
43-42	0.833	-2.035	3.702	1
44-42	0.6	-2.185	3.385	1
45-42	1	-2.756	4.756	1
46-42	1	-1.785	3.785	1
48-42	1.077	-1.679	3.833	0.999
49-42	0	-3.756	3.756	1
50-42	1.333	-1.431	4.098	0.987
51-42	0	-3.756	3.756	1
52-42	1.077	-1.679	3.833	0.999
54-42	1.25	-1.567	4.067	0.996
55-42	1.111	-1.688	3.911	0.999
56-42	1	-1.817	3.817	1
57-42	1.2	-1.709	4.109	0.999
58-42	1.333	-1.733	4.4	0.997
59-42	1	-1.839	3.839	1
60-42	2	-0.969	4.969	0.695
62-42	1	-2.067	4.067	1
66-42	1.5	-1.469	4.469	0.977
44-43	-0.233	-1.605	1.138	1
45-43	0.167	-2.702	3.035	1
46-43	0.167	-1.205	1.538	1
48-43	0.244	-1.067	1.554	1
49-43	-0.833	-3.702	2.035	1
50-43	0.5	-0.828	1.828	1
51-43	-0.833	-3.702	2.035	1
52-43	0.244	-1.067	1.554	1
54-43	0.417	-1.018	1.851	1
55-43	0.278	-1.122	1.678	1
56-43	0.167	-1.268	1.601	1
57-43	0.367	-1.242	1.975	1
58-43	0.5	-1.378	2.378	1
59-43	0.167	-1.311	1.644	1
60-43	1.167	-0.548	2.881	0.676
62-43	0.167	-1.711	2.045	1
66-43	0.667	-1.048	2.381	0.999
45-44	0.4	-2.385	3.185	1
46-44	0.4	-0.788	1.588	1
48-44	0.477	-0.64	1.594	0.998
49-44	-0.6	-3.385	2.185	1
50-44	0.733	-0.404	1.87	0.771
51-44	-0.6	-3.385	2.185	1
52-44	0.477	-0.64	1.594	0.998
54-44	0.65	-0.61	1.91	0.97
55-44	0.511	-0.709	1.731	0.998
56-44	0.4	-0.86	1.66	1
57-44	0.6	-0.855	2.055	0.999
58-44	0.733	-1.015	2.482	0.998
59-44	0.4	-0.909	1.709	1
60-44	1.4	-0.171	2.971	0.158
62-44	0.4	-1.348	2.148	1
66-44	0.9	-0.671	2.471	0.913
46-45	0	-2.785	2.785	1
48-45	0.077	-2.679	2.833	1
49-45	-1	-4.756	2.756	1
50-45	0.333	-2.431	3.098	1
51-45	-1	-4.756	2.756	1
52-45	0.077	-2.679	2.833	1
54-45	0.25	-2.567	3.067	1
55-45	0.111	-2.688	2.911	1
56-45	0	-2.817	2.817	1
57-45	0.2	-2.709	3.109	1
58-45	0.333	-2.733	3.4	1
59-45	0	-2.839	2.839	1
60-45	1	-1.969	3.969	1
62-45	0	-3.067	3.067	1
66-45	0.5	-2.469	3.469	1
48-46	0.077	-1.04	1.194	1
49-46	-1	-3.785	1.785	1
50-46	0.333	-0.804	1.47	1
51-46	-1	-3.785	1.785	1
52-46	0.077	-1.04	1.194	1
54-46	0.25	-1.01	1.51	1
55-46	0.111	-1.109	1.331	1
56-46	0	-1.26	1.26	1
57-46	0.2	-1.255	1.655	1
58-46	0.333	-1.415	2.082	1
59-46	0	-1.309	1.309	1
60-46	1	-0.571	2.571	0.791
62-46	0	-1.748	1.748	1
66-46	0.5	-1.071	2.071	1
49-48	-1.077	-3.833	1.679	0.999
50-48	0.256	-0.807	1.32	1
51-48	-1.077	-3.833	1.679	0.999
52-48	0	-1.042	1.042	1
54-48	0.173	-1.02	1.366	1
55-48	0.034	-1.117	1.186	1
56-48	-0.077	-1.27	1.116	1
57-48	0.123	-1.275	1.521	1
58-48	0.256	-1.445	1.958	1
59-48	-0.077	-1.322	1.168	1
60-48	0.923	-0.595	2.442	0.853
62-48	-0.077	-1.778	1.624	1
66-48	0.423	-1.095	1.942	1
50-49	1.333	-1.431	4.098	0.987
51-49	0	-3.756	3.756	1
52-49	1.077	-1.679	3.833	0.999
54-49	1.25	-1.567	4.067	0.996
55-49	1.111	-1.688	3.911	0.999
56-49	1	-1.817	3.817	1
57-49	1.2	-1.709	4.109	0.999
58-49	1.333	-1.733	4.4	0.997
59-49	1	-1.839	3.839	1
60-49	2	-0.969	4.969	0.695
62-49	1	-2.067	4.067	1
66-49	1.5	-1.469	4.469	0.977
51-50	-1.333	-4.098	1.431	0.987
52-50	-0.256	-1.32	0.807	1
54-50	-0.083	-1.296	1.129	1
55-50	-0.222	-1.393	0.949	1
56-50	-0.333	-1.546	0.879	1
57-50	-0.133	-1.547	1.28	1
58-50	0	-1.714	1.714	1
59-50	-0.333	-1.596	0.93	1
60-50	0.667	-0.867	2.2	0.997
62-50	-0.333	-2.048	1.381	1
66-50	0.167	-1.367	1.7	1
52-51	1.077	-1.679	3.833	0.999
54-51	1.25	-1.567	4.067	0.996
55-51	1.111	-1.688	3.911	0.999
56-51	1	-1.817	3.817	1
57-51	1.2	-1.709	4.109	0.999
58-51	1.333	-1.733	4.4	0.997
59-51	1	-1.839	3.839	1
60-51	2	-0.969	4.969	0.695
62-51	1	-2.067	4.067	1
66-51	1.5	-1.469	4.469	0.977
54-52	0.173	-1.02	1.366	1
55-52	0.034	-1.117	1.186	1
56-52	-0.077	-1.27	1.116	1
57-52	0.123	-1.275	1.521	1
58-52	0.256	-1.445	1.958	1
59-52	-0.077	-1.322	1.168	1
60-52	0.923	-0.595	2.442	0.853
62-52	-0.077	-1.778	1.624	1
66-52	0.423	-1.095	1.942	1
55-54	-0.139	-1.429	1.152	1
56-54	-0.25	-1.578	1.078	1
57-54	-0.05	-1.564	1.464	1
58-54	0.083	-1.715	1.881	1
59-54	-0.25	-1.625	1.125	1
60-54	0.75	-0.876	2.376	0.993
62-54	-0.25	-2.048	1.548	1
66-54	0.25	-1.376	1.876	1
56-55	-0.111	-1.402	1.179	1
57-55	0.089	-1.392	1.57	1
58-55	0.222	-1.548	1.993	1
59-55	-0.111	-1.45	1.227	1
60-55	0.889	-0.707	2.485	0.933
62-55	-0.111	-1.882	1.659	1
66-55	0.389	-1.207	1.985	1
57-56	0.2	-1.314	1.714	1
58-56	0.333	-1.465	2.131	1
59-56	0	-1.375	1.375	1
60-56	1	-0.626	2.626	0.839
62-56	0	-1.798	1.798	1
66-56	0.5	-1.126	2.126	1
58-57	0.133	-1.806	2.073	1
59-57	-0.2	-1.755	1.355	1
60-57	0.8	-0.982	2.582	0.995
62-57	-0.2	-2.14	1.74	1
66-57	0.3	-1.482	2.082	1
59-58	-0.333	-2.166	1.499	1
60-58	0.667	-1.362	2.695	1
62-58	-0.333	-2.502	1.835	1
66-58	0.167	-1.862	2.195	1
60-59	1	-0.665	2.665	0.867
62-59	0	-1.833	1.833	1
66-59	0.5	-1.165	2.165	1
62-60	-1	-3.028	1.028	0.983
66-60	-0.5	-2.378	1.378	1
66-62	0.5	-1.528	2.528	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	26	1.596	0.046
	131

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/12/t12606446406qqy3agwmimgi76/36l501260644599.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/12/t12606446406qqy3agwmimgi76/36l501260644599.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/12/t12606446406qqy3agwmimgi76/441k11260644599.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/12/t12606446406qqy3agwmimgi76/441k11260644599.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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