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Mother's verbal IQ and child's verbal IQ

*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: Fri, 04 Dec 2009 08:12:53 -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/04/t1259939858erlcsvw7wn5k0ij.htm/, Retrieved Fri, 04 Dec 2009 16:17:41 +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/2009/Dec/04/t1259939858erlcsvw7wn5k0ij.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 2 36 2 56 3 48 2 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 2 49 2 42 2 37 2 41 2 30 2 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 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 1 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 1 39 2 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	5 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
RespVar ~ AgeGroup
means	1.5	-0.5	0.5	0.5	0.1	0.1	0.3	0.3	0.5	0.5	0.1	-0.5	0.2	0.423	0.5	0.667	-0.5	0.423	0.375	0.167	0.625	0.1	0.5	0.5	0.25	0.5	1.25

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
AgeGroup	26	10.631	0.409	0.921	0.579
Residuals	133	59.063	0.444

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
31-30	-0.5	-3.315	2.315	1
32-30	0.5	-1.68	2.68	1
34-30	0.5	-1.28	2.28	1
36-30	0.1	-1.589	1.789	1
37-30	0.1	-1.589	1.789	1
39-30	0.3	-1.189	1.789	1
41-30	0.3	-1.189	1.789	1
42-30	0.5	-2.315	3.315	1
43-30	0.5	-1.125	2.125	1
44-30	0.1	-1.389	1.589	1
45-30	-0.5	-3.315	2.315	1
46-30	0.2	-1.289	1.689	1
48-30	0.423	-1.016	1.863	1
49-30	0.5	-2.315	3.315	1
50-30	0.667	-0.787	2.12	0.993
51-30	-0.5	-3.315	2.315	1
52-30	0.423	-1.016	1.863	1
54-30	0.375	-1.167	1.917	1
55-30	0.167	-1.346	1.679	1
56-30	0.625	-0.917	2.167	0.999
57-30	0.1	-1.589	1.789	1
58-30	0.5	-1.423	2.423	1
59-30	0.5	-1.078	2.078	1
60-30	0.25	-1.53	2.03	1
62-30	0.5	-1.423	2.423	1
66-30	1.25	-0.53	3.03	0.615
32-31	1	-2.083	4.083	1
34-31	1	-1.815	3.815	1
36-31	0.6	-2.158	3.358	1
37-31	0.6	-2.158	3.358	1
39-31	0.8	-1.84	3.44	1
41-31	0.8	-1.84	3.44	1
42-31	1	-2.56	4.56	1
43-31	1	-1.719	3.719	1
44-31	0.6	-2.04	3.24	1
45-31	0	-3.56	3.56	1
46-31	0.7	-1.94	3.34	1
48-31	0.923	-1.689	3.536	1
49-31	1	-2.56	4.56	1
50-31	1.167	-1.454	3.787	0.996
51-31	0	-3.56	3.56	1
52-31	0.923	-1.689	3.536	1
54-31	0.875	-1.795	3.545	1
55-31	0.667	-1.987	3.32	1
56-31	1.125	-1.545	3.795	0.998
57-31	0.6	-2.158	3.358	1
58-31	1	-1.907	3.907	1
59-31	1	-1.691	3.691	1
60-31	0.75	-2.065	3.565	1
62-31	1	-1.907	3.907	1
66-31	1.75	-1.065	4.565	0.825
34-32	0	-2.18	2.18	1
36-32	-0.4	-2.506	1.706	1
37-32	-0.4	-2.506	1.706	1
39-32	-0.2	-2.15	1.75	1
41-32	-0.2	-2.15	1.75	1
42-32	0	-3.083	3.083	1
43-32	0	-2.056	2.056	1
44-32	-0.4	-2.35	1.55	1
45-32	-1	-4.083	2.083	1
46-32	-0.3	-2.25	1.65	1
48-32	-0.077	-1.989	1.835	1
49-32	0	-3.083	3.083	1
50-32	0.167	-1.756	2.089	1
51-32	-1	-4.083	2.083	1
52-32	-0.077	-1.989	1.835	1
54-32	-0.125	-2.115	1.865	1
55-32	-0.333	-2.301	1.635	1
56-32	0.125	-1.865	2.115	1
57-32	-0.4	-2.506	1.706	1
58-32	0	-2.298	2.298	1
59-32	0	-2.018	2.018	1
60-32	-0.25	-2.43	1.93	1
62-32	0	-2.298	2.298	1
66-32	0.75	-1.43	2.93	1
36-34	-0.4	-2.089	1.289	1
37-34	-0.4	-2.089	1.289	1
39-34	-0.2	-1.689	1.289	1
41-34	-0.2	-1.689	1.289	1
42-34	0	-2.815	2.815	1
43-34	0	-1.625	1.625	1
44-34	-0.4	-1.889	1.089	1
45-34	-1	-3.815	1.815	1
46-34	-0.3	-1.789	1.189	1
48-34	-0.077	-1.516	1.363	1
49-34	0	-2.815	2.815	1
50-34	0.167	-1.287	1.62	1
51-34	-1	-3.815	1.815	1
52-34	-0.077	-1.516	1.363	1
54-34	-0.125	-1.667	1.417	1
55-34	-0.333	-1.846	1.179	1
56-34	0.125	-1.417	1.667	1
57-34	-0.4	-2.089	1.289	1
58-34	0	-1.923	1.923	1
59-34	0	-1.578	1.578	1
60-34	-0.25	-2.03	1.53	1
62-34	0	-1.923	1.923	1
66-34	0.75	-1.03	2.53	0.998
37-36	0	-1.592	1.592	1
39-36	0.2	-1.179	1.579	1
41-36	0.2	-1.179	1.579	1
42-36	0.4	-2.358	3.158	1
43-36	0.4	-1.124	1.924	1
44-36	0	-1.379	1.379	1
45-36	-0.6	-3.358	2.158	1
46-36	0.1	-1.279	1.479	1
48-36	0.323	-1.002	1.648	1
49-36	0.4	-2.358	3.158	1
50-36	0.567	-0.773	1.907	0.998
51-36	-0.6	-3.358	2.158	1
52-36	0.323	-1.002	1.648	1
54-36	0.275	-1.16	1.71	1
55-36	0.067	-1.338	1.471	1
56-36	0.525	-0.91	1.96	1
57-36	0	-1.592	1.592	1
58-36	0.4	-1.439	2.239	1
59-36	0.4	-1.074	1.874	1
60-36	0.15	-1.539	1.839	1
62-36	0.4	-1.439	2.239	1
66-36	1.15	-0.539	2.839	0.675
39-37	0.2	-1.179	1.579	1
41-37	0.2	-1.179	1.579	1
42-37	0.4	-2.358	3.158	1
43-37	0.4	-1.124	1.924	1
44-37	0	-1.379	1.379	1
45-37	-0.6	-3.358	2.158	1
46-37	0.1	-1.279	1.479	1
48-37	0.323	-1.002	1.648	1
49-37	0.4	-2.358	3.158	1
50-37	0.567	-0.773	1.907	0.998
51-37	-0.6	-3.358	2.158	1
52-37	0.323	-1.002	1.648	1
54-37	0.275	-1.16	1.71	1
55-37	0.067	-1.338	1.471	1
56-37	0.525	-0.91	1.96	1
57-37	0	-1.592	1.592	1
58-37	0.4	-1.439	2.239	1
59-37	0.4	-1.074	1.874	1
60-37	0.15	-1.539	1.839	1
62-37	0.4	-1.439	2.239	1
66-37	1.15	-0.539	2.839	0.675
41-39	0	-1.126	1.126	1
42-39	0.2	-2.44	2.84	1
43-39	0.2	-1.1	1.5	1
44-39	-0.2	-1.326	0.926	1
45-39	-0.8	-3.44	1.84	1
46-39	-0.1	-1.226	1.026	1
48-39	0.123	-0.936	1.182	1
49-39	0.2	-2.44	2.84	1
50-39	0.367	-0.711	1.445	1
51-39	-0.8	-3.44	1.84	1
52-39	0.123	-0.936	1.182	1
54-39	0.075	-1.119	1.269	1
55-39	-0.133	-1.29	1.023	1
56-39	0.325	-0.869	1.519	1
57-39	-0.2	-1.579	1.179	1
58-39	0.2	-1.457	1.857	1
59-39	0.2	-1.041	1.441	1
60-39	-0.05	-1.539	1.439	1
62-39	0.2	-1.457	1.857	1
66-39	0.95	-0.539	2.439	0.788
42-41	0.2	-2.44	2.84	1
43-41	0.2	-1.1	1.5	1
44-41	-0.2	-1.326	0.926	1
45-41	-0.8	-3.44	1.84	1
46-41	-0.1	-1.226	1.026	1
48-41	0.123	-0.936	1.182	1
49-41	0.2	-2.44	2.84	1
50-41	0.367	-0.711	1.445	1
51-41	-0.8	-3.44	1.84	1
52-41	0.123	-0.936	1.182	1
54-41	0.075	-1.119	1.269	1
55-41	-0.133	-1.29	1.023	1
56-41	0.325	-0.869	1.519	1
57-41	-0.2	-1.579	1.179	1
58-41	0.2	-1.457	1.857	1
59-41	0.2	-1.041	1.441	1
60-41	-0.05	-1.539	1.439	1
62-41	0.2	-1.457	1.857	1
66-41	0.95	-0.539	2.439	0.788
43-42	0	-2.719	2.719	1
44-42	-0.4	-3.04	2.24	1
45-42	-1	-4.56	2.56	1
46-42	-0.3	-2.94	2.34	1
48-42	-0.077	-2.689	2.536	1
49-42	0	-3.56	3.56	1
50-42	0.167	-2.454	2.787	1
51-42	-1	-4.56	2.56	1
52-42	-0.077	-2.689	2.536	1
54-42	-0.125	-2.795	2.545	1
55-42	-0.333	-2.987	2.32	1
56-42	0.125	-2.545	2.795	1
57-42	-0.4	-3.158	2.358	1
58-42	0	-2.907	2.907	1
59-42	0	-2.691	2.691	1
60-42	-0.25	-3.065	2.565	1
62-42	0	-2.907	2.907	1
66-42	0.75	-2.065	3.565	1
44-43	-0.4	-1.7	0.9	1
45-43	-1	-3.719	1.719	1
46-43	-0.3	-1.6	1	1
48-43	-0.077	-1.319	1.166	1
49-43	0	-2.719	2.719	1
50-43	0.167	-1.092	1.425	1
51-43	-1	-3.719	1.719	1
52-43	-0.077	-1.319	1.166	1
54-43	-0.125	-1.485	1.235	1
55-43	-0.333	-1.66	0.993	1
56-43	0.125	-1.235	1.485	1
57-43	-0.4	-1.924	1.124	1
58-43	0	-1.78	1.78	1
59-43	0	-1.401	1.401	1
60-43	-0.25	-1.875	1.375	1
62-43	0	-1.78	1.78	1
66-43	0.75	-0.875	2.375	0.993
45-44	-0.6	-3.24	2.04	1
46-44	0.1	-1.026	1.226	1
48-44	0.323	-0.736	1.382	1
49-44	0.4	-2.24	3.04	1
50-44	0.567	-0.511	1.645	0.964
51-44	-0.6	-3.24	2.04	1
52-44	0.323	-0.736	1.382	1
54-44	0.275	-0.919	1.469	1
55-44	0.067	-1.09	1.223	1
56-44	0.525	-0.669	1.719	0.996
57-44	0	-1.379	1.379	1
58-44	0.4	-1.257	2.057	1
59-44	0.4	-0.841	1.641	1
60-44	0.15	-1.339	1.639	1
62-44	0.4	-1.257	2.057	1
66-44	1.15	-0.339	2.639	0.413
46-45	0.7	-1.94	3.34	1
48-45	0.923	-1.689	3.536	1
49-45	1	-2.56	4.56	1
50-45	1.167	-1.454	3.787	0.996
51-45	0	-3.56	3.56	1
52-45	0.923	-1.689	3.536	1
54-45	0.875	-1.795	3.545	1
55-45	0.667	-1.987	3.32	1
56-45	1.125	-1.545	3.795	0.998
57-45	0.6	-2.158	3.358	1
58-45	1	-1.907	3.907	1
59-45	1	-1.691	3.691	1
60-45	0.75	-2.065	3.565	1
62-45	1	-1.907	3.907	1
66-45	1.75	-1.065	4.565	0.825
48-46	0.223	-0.836	1.282	1
49-46	0.3	-2.34	2.94	1
50-46	0.467	-0.611	1.545	0.997
51-46	-0.7	-3.34	1.94	1
52-46	0.223	-0.836	1.282	1
54-46	0.175	-1.019	1.369	1
55-46	-0.033	-1.19	1.123	1
56-46	0.425	-0.769	1.619	1
57-46	-0.1	-1.479	1.279	1
58-46	0.3	-1.357	1.957	1
59-46	0.3	-0.941	1.541	1
60-46	0.05	-1.439	1.539	1
62-46	0.3	-1.357	1.957	1
66-46	1.05	-0.439	2.539	0.606
49-48	0.077	-2.536	2.689	1
50-48	0.244	-0.764	1.251	1
51-48	-0.923	-3.536	1.689	1
52-48	0	-0.987	0.987	1
54-48	-0.048	-1.179	1.083	1
55-48	-0.256	-1.348	0.835	1
56-48	0.202	-0.929	1.333	1
57-48	-0.323	-1.648	1.002	1
58-48	0.077	-1.536	1.689	1
59-48	0.077	-1.103	1.257	1
60-48	-0.173	-1.613	1.266	1
62-48	0.077	-1.536	1.689	1
66-48	0.827	-0.613	2.266	0.911
50-49	0.167	-2.454	2.787	1
51-49	-1	-4.56	2.56	1
52-49	-0.077	-2.689	2.536	1
54-49	-0.125	-2.795	2.545	1
55-49	-0.333	-2.987	2.32	1
56-49	0.125	-2.545	2.795	1
57-49	-0.4	-3.158	2.358	1
58-49	0	-2.907	2.907	1
59-49	0	-2.691	2.691	1
60-49	-0.25	-3.065	2.565	1
62-49	0	-2.907	2.907	1
66-49	0.75	-2.065	3.565	1
51-50	-1.167	-3.787	1.454	0.996
52-50	-0.244	-1.251	0.764	1
54-50	-0.292	-1.441	0.857	1
55-50	-0.5	-1.61	0.61	0.995
56-50	-0.042	-1.191	1.107	1
57-50	-0.567	-1.907	0.773	0.998
58-50	-0.167	-1.792	1.458	1
59-50	-0.167	-1.364	1.031	1
60-50	-0.417	-1.87	1.037	1
62-50	-0.167	-1.792	1.458	1
66-50	0.583	-0.87	2.037	0.999
52-51	0.923	-1.689	3.536	1
54-51	0.875	-1.795	3.545	1
55-51	0.667	-1.987	3.32	1
56-51	1.125	-1.545	3.795	0.998
57-51	0.6	-2.158	3.358	1
58-51	1	-1.907	3.907	1
59-51	1	-1.691	3.691	1
60-51	0.75	-2.065	3.565	1
62-51	1	-1.907	3.907	1
66-51	1.75	-1.065	4.565	0.825
54-52	-0.048	-1.179	1.083	1
55-52	-0.256	-1.348	0.835	1
56-52	0.202	-0.929	1.333	1
57-52	-0.323	-1.648	1.002	1
58-52	0.077	-1.536	1.689	1
59-52	0.077	-1.103	1.257	1
60-52	-0.173	-1.613	1.266	1
62-52	0.077	-1.536	1.689	1
66-52	0.827	-0.613	2.266	0.911
55-54	-0.208	-1.432	1.015	1
56-54	0.25	-1.009	1.509	1
57-54	-0.275	-1.71	1.16	1
58-54	0.125	-1.579	1.829	1
59-54	0.125	-1.178	1.428	1
60-54	-0.125	-1.667	1.417	1
62-54	0.125	-1.579	1.829	1
66-54	0.875	-0.667	2.417	0.92
56-55	0.458	-0.765	1.682	1
57-55	-0.067	-1.471	1.338	1
58-55	0.333	-1.345	2.012	1
59-55	0.333	-0.935	1.602	1
60-55	0.083	-1.429	1.596	1
62-55	0.333	-1.345	2.012	1
66-55	1.083	-0.429	2.596	0.574
57-56	-0.525	-1.96	0.91	1
58-56	-0.125	-1.829	1.579	1
59-56	-0.125	-1.428	1.178	1
60-56	-0.375	-1.917	1.167	1
62-56	-0.125	-1.829	1.579	1
66-56	0.625	-0.917	2.167	0.999
58-57	0.4	-1.439	2.239	1
59-57	0.4	-1.074	1.874	1
60-57	0.15	-1.539	1.839	1
62-57	0.4	-1.439	2.239	1
66-57	1.15	-0.539	2.839	0.675
59-58	0	-1.737	1.737	1
60-58	-0.25	-2.173	1.673	1
62-58	0	-2.056	2.056	1
66-58	0.75	-1.173	2.673	0.999
60-59	-0.25	-1.828	1.328	1
62-59	0	-1.737	1.737	1
66-59	0.75	-0.828	2.328	0.989
62-60	0.25	-1.673	2.173	1
66-60	1	-0.78	2.78	0.928
66-62	0.75	-1.173	2.673	0.999

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	26	0.778	0.769
	133

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939858erlcsvw7wn5k0ij/3qex01259939567.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939858erlcsvw7wn5k0ij/3qex01259939567.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939858erlcsvw7wn5k0ij/4cnj31259939567.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939858erlcsvw7wn5k0ij/4cnj31259939567.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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