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maternal warmth verbal IQ-30months

*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: Mon, 14 Dec 2009 16:39:43 -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/15/t1260834114i57ylp62bq844v2.htm/, Retrieved Tue, 15 Dec 2009 00:41:57 +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/15/t1260834114i57ylp62bq844v2.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 «

3 36 6 36 8 56 8 48 7 32 5 44 7 39 8 34 9 41 9 50 3 39 9 62 7 52 9 37 8 50 6 41 7 55 8 41 9 56 7 39 6 52 8 46 7 44 7 48 8 41 9 50 9 50 7 44 4 52 7 54 7 44 9 52 7 37 9 52 10 50 5 36 6 50 9 52 9 55 8 31 6 36 6 49 5 42 8 37 8 41 5 30 6 52 9 30 8 41 4 44 8 66 9 48 7 43 7 57 6 46 9 54 9 48 8 48 4 52 6 62 10 58 8 58 7 62 7 48 8 46 3 34 8 66 10 52 7 55 5 55 10 57 5 56 8 55 9 56 6 54 9 55 8 46 5 52 8 32 3 44 7 46 8 59 10 46 9 46 10 54 9 66 8 56 8 59 8 57 9 52 4 48 6 44 7 41 4 50 9 48 7 48 8 59 0 34 8 46 7 54 7 55 9 54 8 59 8 44 9 54 9 52 10 66 7 44 8 57 5 39 9 60 8 45 7 41 8 50 8 39 7 43 6 48 7 37 7 58 6 46 6 43 7 44 9 34 6 30 10 50 4 39 8 37 7 55 10 48 0 41 5 39 9 36 8 43 9 50 8 55 8 43 9 60 8 48 9 30 7 43 6 39 8 52 6 39 5 39 3 56 6 59 8 46 7 57 8 50 6 54 9 50 9 60 10 59 7 41 5 48 8 59 9 60 8 56 8 56 4 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	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
mternalwrmth ~ verbalIQ30
means	7.25	0.75	0.25	-2.25	-1.45	0.55	-1.65	-0.45	-2.25	-0.083	-1.15	0.75	0.55	0.212	-1.25	1	-3.25	0.058	0.625	0.194	0	0.75	1.083	0.75	1.75	0.083	1.5

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
verbalIQ30	26	143.861	5.533	1.781	0.018
Residuals	133	413.114	3.106

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
31-30	0.75	-6.694	8.194	1
32-30	0.25	-5.516	6.016	1
34-30	-2.25	-6.958	2.458	0.988
36-30	-1.45	-5.916	3.016	1
37-30	0.55	-3.916	5.016	1
39-30	-1.65	-5.589	2.289	0.998
41-30	-0.45	-4.389	3.489	1
42-30	-2.25	-9.694	5.194	1
43-30	-0.083	-4.381	4.214	1
44-30	-1.15	-5.089	2.789	1
45-30	0.75	-6.694	8.194	1
46-30	0.55	-3.389	4.489	1
48-30	0.212	-3.595	4.018	1
49-30	-1.25	-8.694	6.194	1
50-30	1	-2.844	4.844	1
51-30	-3.25	-10.694	4.194	0.997
52-30	0.058	-3.749	3.865	1
54-30	0.625	-3.452	4.702	1
55-30	0.194	-3.807	4.195	1
56-30	0	-4.077	4.077	1
57-30	0.75	-3.716	5.216	1
58-30	1.083	-4.002	6.168	1
59-30	0.75	-3.423	4.923	1
60-30	1.75	-2.958	6.458	1
62-30	0.083	-5.002	5.168	1
66-30	1.5	-3.208	6.208	1
32-31	-0.5	-8.654	7.654	1
34-31	-3	-10.444	4.444	0.999
36-31	-2.2	-9.493	5.093	1
37-31	-0.2	-7.493	7.093	1
39-31	-2.4	-9.383	4.583	1
41-31	-1.2	-8.183	5.783	1
42-31	-3	-12.416	6.416	1
43-31	-0.833	-8.025	6.358	1
44-31	-1.9	-8.883	5.083	1
45-31	0	-9.416	9.416	1
46-31	-0.2	-7.183	6.783	1
48-31	-0.538	-7.448	6.371	1
49-31	-2	-11.416	7.416	1
50-31	0.25	-6.68	7.18	1
51-31	-4	-13.416	5.416	0.998
52-31	-0.692	-7.602	6.217	1
54-31	-0.125	-7.187	6.937	1
55-31	-0.556	-7.574	6.463	1
56-31	-0.75	-7.812	6.312	1
57-31	0	-7.293	7.293	1
58-31	0.333	-7.355	8.021	1
59-31	0	-7.118	7.118	1
60-31	1	-6.444	8.444	1
62-31	-0.667	-8.355	7.021	1
66-31	0.75	-6.694	8.194	1
34-32	-2.5	-8.266	3.266	0.997
36-32	-1.7	-7.27	3.87	1
37-32	0.3	-5.27	5.87	1
39-32	-1.9	-7.057	3.257	1
41-32	-0.7	-5.857	4.457	1
42-32	-2.5	-10.654	5.654	1
43-32	-0.333	-5.77	5.103	1
44-32	-1.4	-6.557	3.757	1
45-32	0.5	-7.654	8.654	1
46-32	0.3	-4.857	5.457	1
48-32	-0.038	-5.096	5.019	1
49-32	-1.5	-9.654	6.654	1
50-32	0.75	-4.335	5.835	1
51-32	-3.5	-11.654	4.654	0.997
52-32	-0.192	-5.249	4.865	1
54-32	0.375	-4.889	5.639	1
55-32	-0.056	-5.26	5.149	1
56-32	-0.25	-5.514	5.014	1
57-32	0.5	-5.07	6.07	1
58-32	0.833	-5.245	6.911	1
59-32	0.5	-4.838	5.838	1
60-32	1.5	-4.266	7.266	1
62-32	-0.167	-6.245	5.911	1
66-32	1.25	-4.516	7.016	1
36-34	0.8	-3.666	5.266	1
37-34	2.8	-1.666	7.266	0.813
39-34	0.6	-3.339	4.539	1
41-34	1.8	-2.139	5.739	0.994
42-34	0	-7.444	7.444	1
43-34	2.167	-2.131	6.464	0.978
44-34	1.1	-2.839	5.039	1
45-34	3	-4.444	10.444	0.999
46-34	2.8	-1.139	6.739	0.589
48-34	2.462	-1.345	6.268	0.767
49-34	1	-6.444	8.444	1
50-34	3.25	-0.594	7.094	0.238
51-34	-1	-8.444	6.444	1
52-34	2.308	-1.499	6.115	0.857
54-34	2.875	-1.202	6.952	0.606
55-34	2.444	-1.557	6.445	0.847
56-34	2.25	-1.827	6.327	0.939
57-34	3	-1.466	7.466	0.701
58-34	3.333	-1.752	8.418	0.744
59-34	3	-1.173	7.173	0.566
60-34	4	-0.708	8.708	0.23
62-34	2.333	-2.752	7.418	0.993
66-34	3.75	-0.958	8.458	0.349
37-36	2	-2.211	6.211	0.989
39-36	-0.2	-3.847	3.447	1
41-36	1	-2.647	4.647	1
42-36	-0.8	-8.093	6.493	1
43-36	1.367	-2.665	5.398	1
44-36	0.3	-3.347	3.947	1
45-36	2.2	-5.093	9.493	1
46-36	2	-1.647	5.647	0.943
48-36	1.662	-1.842	5.165	0.99
49-36	0.2	-7.093	7.493	1
50-36	2.45	-1.094	5.994	0.646
51-36	-1.8	-9.093	5.493	1
52-36	1.508	-1.996	5.011	0.997
54-36	2.075	-1.721	5.871	0.945
55-36	1.644	-2.069	5.358	0.996
56-36	1.45	-2.346	5.246	1
57-36	2.2	-2.011	6.411	0.966
58-36	2.533	-2.329	7.396	0.967
59-36	2.2	-1.699	6.099	0.924
60-36	3.2	-1.266	7.666	0.573
62-36	1.533	-3.329	6.396	1
66-36	2.95	-1.516	7.416	0.731
39-37	-2.2	-5.847	1.447	0.862
41-37	-1	-4.647	2.647	1
42-37	-2.8	-10.093	4.493	1
43-37	-0.633	-4.665	3.398	1
44-37	-1.7	-5.347	1.947	0.992
45-37	0.2	-7.093	7.493	1
46-37	0	-3.647	3.647	1
48-37	-0.338	-3.842	3.165	1
49-37	-1.8	-9.093	5.493	1
50-37	0.45	-3.094	3.994	1
51-37	-3.8	-11.093	3.493	0.967
52-37	-0.492	-3.996	3.011	1
54-37	0.075	-3.721	3.871	1
55-37	-0.356	-4.069	3.358	1
56-37	-0.55	-4.346	3.246	1
57-37	0.2	-4.011	4.411	1
58-37	0.533	-4.329	5.396	1
59-37	0.2	-3.699	4.099	1
60-37	1.2	-3.266	5.666	1
62-37	-0.467	-5.329	4.396	1
66-37	0.95	-3.516	5.416	1
41-39	1.2	-1.778	4.178	0.999
42-39	-0.6	-7.583	6.383	1
43-39	1.567	-1.872	5.005	0.994
44-39	0.5	-2.478	3.478	1
45-39	2.4	-4.583	9.383	1
46-39	2.2	-0.778	5.178	0.507
48-39	1.862	-0.939	4.662	0.72
49-39	0.4	-6.583	7.383	1
50-39	2.65	-0.201	5.501	0.108
51-39	-1.6	-8.583	5.383	1
52-39	1.708	-1.093	4.508	0.85
54-39	2.275	-0.883	5.433	0.562
55-39	1.844	-1.215	4.904	0.863
56-39	1.65	-1.508	4.808	0.966
57-39	2.4	-1.247	6.047	0.737
58-39	2.733	-1.65	7.116	0.821
59-39	2.4	-0.881	5.681	0.529
60-39	3.4	-0.539	7.339	0.204
62-39	1.733	-2.65	6.116	0.999
66-39	3.15	-0.789	7.089	0.341
42-41	-1.8	-8.783	5.183	1
43-41	0.367	-3.072	3.805	1
44-41	-0.7	-3.678	2.278	1
45-41	1.2	-5.783	8.183	1
46-41	1	-1.978	3.978	1
48-41	0.662	-2.139	3.462	1
49-41	-0.8	-7.783	6.183	1
50-41	1.45	-1.401	4.301	0.975
51-41	-2.8	-9.783	4.183	0.999
52-41	0.508	-2.293	3.308	1
54-41	1.075	-2.083	4.233	1
55-41	0.644	-2.415	3.704	1
56-41	0.45	-2.708	3.608	1
57-41	1.2	-2.447	4.847	1
58-41	1.533	-2.85	5.916	1
59-41	1.2	-2.081	4.481	1
60-41	2.2	-1.739	6.139	0.932
62-41	0.533	-3.85	4.916	1
66-41	1.95	-1.989	5.889	0.982
43-42	2.167	-5.025	9.358	1
44-42	1.1	-5.883	8.083	1
45-42	3	-6.416	12.416	1
46-42	2.8	-4.183	9.783	0.999
48-42	2.462	-4.448	9.371	1
49-42	1	-8.416	10.416	1
50-42	3.25	-3.68	10.18	0.991
51-42	-1	-10.416	8.416	1
52-42	2.308	-4.602	9.217	1
54-42	2.875	-4.187	9.937	0.999
55-42	2.444	-4.574	9.463	1
56-42	2.25	-4.812	9.312	1
57-42	3	-4.293	10.293	0.999
58-42	3.333	-4.355	11.021	0.997
59-42	3	-4.118	10.118	0.998
60-42	4	-3.444	11.444	0.954
62-42	2.333	-5.355	10.021	1
66-42	3.75	-3.694	11.194	0.978
44-43	-1.067	-4.505	2.372	1
45-43	0.833	-6.358	8.025	1
46-43	0.633	-2.805	4.072	1
48-43	0.295	-2.991	3.581	1
49-43	-1.167	-8.358	6.025	1
50-43	1.083	-2.246	4.412	1
51-43	-3.167	-10.358	4.025	0.996
52-43	0.141	-3.145	3.427	1
54-43	0.708	-2.887	4.304	1
55-43	0.278	-3.231	3.787	1
56-43	0.083	-3.512	3.679	1
57-43	0.833	-3.198	4.865	1
58-43	1.167	-3.541	5.875	1
59-43	0.833	-2.871	4.538	1
60-43	1.833	-2.464	6.131	0.998
62-43	0.167	-4.541	4.875	1
66-43	1.583	-2.714	5.881	1
45-44	1.9	-5.083	8.883	1
46-44	1.7	-1.278	4.678	0.916
48-44	1.362	-1.439	4.162	0.986
49-44	-0.1	-7.083	6.883	1
50-44	2.15	-0.701	5.001	0.463
51-44	-2.1	-9.083	4.883	1
52-44	1.208	-1.593	4.008	0.997
54-44	1.775	-1.383	4.933	0.927
55-44	1.344	-1.715	4.404	0.996
56-44	1.15	-2.008	4.308	1
57-44	1.9	-1.747	5.547	0.967
58-44	2.233	-2.15	6.616	0.975
59-44	1.9	-1.381	5.181	0.904
60-44	2.9	-1.039	6.839	0.515
62-44	1.233	-3.15	5.616	1
66-44	2.65	-1.289	6.589	0.698
46-45	-0.2	-7.183	6.783	1
48-45	-0.538	-7.448	6.371	1
49-45	-2	-11.416	7.416	1
50-45	0.25	-6.68	7.18	1
51-45	-4	-13.416	5.416	0.998
52-45	-0.692	-7.602	6.217	1
54-45	-0.125	-7.187	6.937	1
55-45	-0.556	-7.574	6.463	1
56-45	-0.75	-7.812	6.312	1
57-45	0	-7.293	7.293	1
58-45	0.333	-7.355	8.021	1
59-45	0	-7.118	7.118	1
60-45	1	-6.444	8.444	1
62-45	-0.667	-8.355	7.021	1
66-45	0.75	-6.694	8.194	1
48-46	-0.338	-3.139	2.462	1
49-46	-1.8	-8.783	5.183	1
50-46	0.45	-2.401	3.301	1
51-46	-3.8	-10.783	3.183	0.948
52-46	-0.492	-3.293	2.308	1
54-46	0.075	-3.083	3.233	1
55-46	-0.356	-3.415	2.704	1
56-46	-0.55	-3.708	2.608	1
57-46	0.2	-3.447	3.847	1
58-46	0.533	-3.85	4.916	1
59-46	0.2	-3.081	3.481	1
60-46	1.2	-2.739	5.139	1
62-46	-0.467	-4.85	3.916	1
66-46	0.95	-2.989	4.889	1
49-48	-1.462	-8.371	5.448	1
50-48	0.788	-1.877	3.454	1
51-48	-3.462	-10.371	3.448	0.979
52-48	-0.154	-2.765	2.458	1
54-48	0.413	-2.578	3.405	1
55-48	-0.017	-2.904	2.87	1
56-48	-0.212	-3.203	2.78	1
57-48	0.538	-2.965	4.042	1
58-48	0.872	-3.393	5.136	1
59-48	0.538	-2.583	3.66	1
60-48	1.538	-2.268	5.345	0.999
62-48	-0.128	-4.393	4.136	1
66-48	1.288	-2.518	5.095	1
50-49	2.25	-4.68	9.18	1
51-49	-2	-11.416	7.416	1
52-49	1.308	-5.602	8.217	1
54-49	1.875	-5.187	8.937	1
55-49	1.444	-5.574	8.463	1
56-49	1.25	-5.812	8.312	1
57-49	2	-5.293	9.293	1
58-49	2.333	-5.355	10.021	1
59-49	2	-5.118	9.118	1
60-49	3	-4.444	10.444	0.999
62-49	1.333	-6.355	9.021	1
66-49	2.75	-4.694	10.194	1
51-50	-4.25	-11.18	2.68	0.843
52-50	-0.942	-3.608	1.723	1
54-50	-0.375	-3.414	2.664	1
55-50	-0.806	-3.741	2.13	1
56-50	-1	-4.039	2.039	1
57-50	-0.25	-3.794	3.294	1
58-50	0.083	-4.214	4.381	1
59-50	-0.25	-3.417	2.917	1
60-50	0.75	-3.094	4.594	1
62-50	-0.917	-5.214	3.381	1
66-50	0.5	-3.344	4.344	1
52-51	3.308	-3.602	10.217	0.988
54-51	3.875	-3.187	10.937	0.943
55-51	3.444	-3.574	10.463	0.984
56-51	3.25	-3.812	10.312	0.993
57-51	4	-3.293	11.293	0.943
58-51	4.333	-3.355	12.021	0.925
59-51	4	-3.118	11.118	0.927
60-51	5	-2.444	12.444	0.701
62-51	3.333	-4.355	11.021	0.997
66-51	4.75	-2.694	12.194	0.788
54-52	0.567	-2.425	3.559	1
55-52	0.137	-2.75	3.024	1
56-52	-0.058	-3.05	2.934	1
57-52	0.692	-2.811	4.196	1
58-52	1.026	-3.239	5.29	1
59-52	0.692	-2.429	3.814	1
60-52	1.692	-2.115	5.499	0.996
62-52	0.026	-4.239	4.29	1
66-52	1.442	-2.365	5.249	1
55-54	-0.431	-3.666	2.805	1
56-54	-0.625	-3.954	2.704	1
57-54	0.125	-3.671	3.921	1
58-54	0.458	-4.049	4.966	1
59-54	0.125	-3.321	3.571	1
60-54	1.125	-2.952	5.202	1
62-54	-0.542	-5.049	3.966	1
66-54	0.875	-3.202	4.952	1
56-55	-0.194	-3.43	3.041	1
57-55	0.556	-3.158	4.269	1
58-55	0.889	-3.55	5.328	1
59-55	0.556	-2.8	3.911	1
60-55	1.556	-2.445	5.557	0.999
62-55	-0.111	-4.55	4.328	1
66-55	1.306	-2.695	5.307	1
57-56	0.75	-3.046	4.546	1
58-56	1.083	-3.424	5.591	1
59-56	0.75	-2.696	4.196	1
60-56	1.75	-2.327	5.827	0.997
62-56	0.083	-4.424	4.591	1
66-56	1.5	-2.577	5.577	1
58-57	0.333	-4.529	5.196	1
59-57	0	-3.899	3.899	1
60-57	1	-3.466	5.466	1
62-57	-0.667	-5.529	4.196	1
66-57	0.75	-3.716	5.216	1
59-58	-0.333	-4.928	4.261	1
60-58	0.667	-4.418	5.752	1
62-58	-1	-6.436	4.436	1
66-58	0.417	-4.668	5.502	1
60-59	1	-3.173	5.173	1
62-59	-0.667	-5.261	3.928	1
66-59	0.75	-3.423	4.923	1
62-60	-1.667	-6.752	3.418	1
66-60	-0.25	-4.958	4.458	1
66-62	1.417	-3.668	6.502	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	26	1.347	0.14
	133

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260834114i57ylp62bq844v2/302nv1260833977.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260834114i57ylp62bq844v2/302nv1260833977.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260834114i57ylp62bq844v2/4vo7f1260833977.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t1260834114i57ylp62bq844v2/4vo7f1260833977.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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