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Topic: Interpretation of coefficients in multiple regressions which model
linear dependence on an IV

Replies: 146   Last Post: Dec 15, 2012 6:44 PM

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Ray Koopman

Posts: 3,383
Registered: 12/7/04
Re: Sparseness of b1 data ...
Posted: Dec 4, 2012 11:50 PM
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On Dec 3, 9:38 pm, djh <halitsk...@att.net> wrote:
> You wrote:
>
> ?You should probably check them against what you get?
>
> I spot checked against various raw detail files, and I didn?t find any
> anomalies.
>
> You wrote:
>
> ?It looks like B1 is going to give problems.?
>
> You can probably decide this question by looking at the table at the
> end of this post.
>
> To understand this table, you need only realize that to do our subset/
> method 2-ways per set per fold per SINGLETON len interval, we need to
> have data for a given triple (set, fold, len) in all four categories
> determined by subset and method, namely NS, NC, RS, and RC. And the
> table shows the counts for the only b1 triples (set, fold, len) for
> which all four of NS,NC,RS,RC are non-empty.
>
> So, if you think the counts in the following table are high enough to
> allow us to operate on b1, then we?re OK. But if you think they?re
> too low, I can very likely increase the counts by getting more
> underlying b1 data ... I distinctly recall being conservative when I
> picked the b1 proteins and associated messages by assuming that high
> amino acid identity meant high codon identity, and this is not
> necessarily the case due to the fact that many changes of codons do
> not change amino acid identity (e.g. changing att to atc still yields
> the amino acid I = ILE = Isoleucine.
>
> Please let me know what you think ? it won?t be a huge detour to try
> and pick-up more b1 data if you think the counts in the table below
> are too low to allow you to operate satisfactorily.
>
> Finally, what?s very interesting about b1 proteins is that they?re
> immunoglobulins, i.e. proteins which play a role in immune systems by
> mutating to meet the challenge posed by new antigens (invaders.) So
> given the fact that it?s the job of b1 proteins to mutate, it?s
> actually surprising we?re getting any counts at all ... in effect, by
> their very nature, b1 proteins push the limits of the domain over
> which we can expect our hypotheses to hold ...
>
> Table:
>
> Sets F Len NS NC RS RC
>
> 1:R1 b1 63 14 14 12 12
> 1:R1 b1 84 15 14 16 15
> 2:R2 b1 25 20 19 24 15
> 2:R2 b1 27 15 15 29 24
> 2:R2 b1 28 14 12 16 15
> 2:R2 b1 30 14 15 14 12
> 2:R2 b1 33 19 12 24 35
> 2:R2 b1 35 17 16 28 27
> 2:R2 b1 42 19 18 12 14
> 2:R2 b1 50 13 14 12 12
> 2:R2 b1 54 12 13 24 24
> 2:R2 b1 64 15 16 16 17
> 2:R2 b1 65 16 16 21 20
> 2:R2 b1 66 13 14 15 15
> 2:R2 b1 89 14 14 24 23
> 2:R2 b1 91 12 12 22 21
> 2:R2 b1 92 19 18 18 18
> 2:R2 b1 95 16 16 22 22
> 2:R2 b1 96 18 18 25 25
> 2:R2 b1 97 12 12 22 19
> 2:R2 b1 98 17 17 25 25
> 2:R2 b1 99 17 17 24 21
> 2:R2 b1 100 16 15 14 13
> 2:R2 b1 103 14 14 17 17
> 2:R2 b1 105 12 12 14 13
> 2:R2 b1 106 14 13 24 23
> 2:R2 b1 108 15 14 16 15
> 2:R2 b1 109 14 12 16 16
> 3:R3 b1 43 15 15 24 22


Yes, I know: the actual n's are 3 bigger than those above.

There are many different rules of thumb for minimum sample size
in regression. The most frequently mentioned rule is n >= 10k.
The most liberal one that I've heard is n >= 5k; by that we would
need n >= 75 in every cell, which ain't about to happen. So if you
can bump up the n's in the smallest cells without too much extra
effort you should probably do it, but otherwise I can live with
what we've got.

Here are the cell n's again, reorganized to make it
easier to see which Subset x MoSS | Fold x Set x Length
conditional 2-way interactions can be estimated.
____________________________________________________________

a1
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 36 47 34 41 75 93 87 94 31 36 28 40
25 48 66 50 48 83 91 84 86 35 36 26 31
26 30 44 47 45 68 83 95 100 30 29 26 31
27 52 58 39 46 80 95 97 106 27 35 37 34
28 58 64 31 34 79 76 104 98 26 37 33 35
29 65 74 42 44 112 100 91 95 45 54 29 29
30 55 64 34 33 80 82 100 93 34 38 37 36
31 50 65 56 49 84 71 88 95 21 28 34 37
32 37 47 35 40 98 83 85 90 33 31 33 33
33 48 54 43 45 101 100 76 90 43 42 44 43
34 56 73 35 32 83 82 90 92 27 27 34 30
35 54 59 38 35 86 84 70 68 32 31 41 33
36 43 57 33 32 68 67 85 86 23 21 31 28
37 57 68 34 39 95 95 75 78 24 27 16 25
38 33 38 30 26 70 74 74 76 43 44 23 31
39 28 30 26 22 66 64 72 74 24 24 43 42
40 40 46 39 39 75 78 65 63 51 48 29 25
41 29 32 24 28 75 75 65 67 27 30 29 24
42 31 31 44 38 64 65 66 68 19 19 34 38
43 27 33 38 38 41 44 57 58 26 25 29 31
44 32 35 35 34 66 65 51 53 35 35 21 22
45 29 29 43 46 51 57 74 83 25 25 24 27
46 33 30 27 22 56 55 56 56 25 20 36 36
47 40 45 25 23 75 74 59 63 22 23 - -
48 32 38 30 29 75 74 64 62 28 30 30 28
49 39 39 27 29 59 59 49 50 20 22 28 30
50 38 40 21 22 71 72 58 55 23 33 20 18
51 42 45 28 26 65 68 63 66 16 21 26 20
52 38 38 32 30 67 69 54 56 33 34 18 19
53 27 33 21 25 54 55 63 63 26 27 23 25
54 30 33 29 32 54 56 51 52 21 23 29 27
55 29 31 22 25 52 55 53 55 22 23 22 20
56 28 31 27 29 59 61 48 49 19 16 28 26
57 34 35 - - 53 54 43 45 22 23 21 20
58 32 32 32 36 59 57 47 45 22 25 17 17
59 24 24 27 21 42 42 38 39 - - 16 15
60 32 34 21 22 43 43 45 47 19 19 18 21
61 35 39 25 27 59 61 38 42 28 29 19 20
62 24 24 21 21 46 49 59 64 20 21 30 32
63 27 28 28 27 60 63 41 42 19 17 16 17
64 23 24 - - 43 45 44 44 16 - 25 25
65 22 21 21 22 39 42 63 63 18 19 - -
66 34 35 36 37 58 58 54 58 16 17 19 20
67 39 40 28 31 48 49 50 51 - 19 24 24
68 16 19 15 17 37 39 40 39 17 17 - -
69 30 34 22 20 43 42 41 46 19 21 15 -
70 38 39 16 - 66 66 34 31 21 24 - -
71 24 24 20 24 62 66 30 28 - - 20 19
72 30 31 - - 42 43 29 32 - - 15 15
73 29 31 20 21 39 41 34 35 15 15 - -
74 23 25 17 19 35 37 40 42 16 16 17 16
75 17 20 15 15 43 44 27 30 17 21 19 -
76 22 22 17 15 34 34 29 29 - - - -
77 24 28 15 15 32 34 29 28 - - 15 -
78 29 30 - - 45 46 29 32 - - - -
79 19 19 - - 39 38 22 23 16 19 19 20
80 30 31 30 33 51 52 36 38 19 19 - -
81 25 26 - - 31 32 17 17 16 22 - -
82 22 24 15 - 32 33 32 31 - - 22 22
83 18 19 21 25 29 30 34 36 - - - -
84 27 27 15 17 36 38 36 39 - - - -
85 16 18 - - 24 24 27 30 19 21 19 19
86 20 21 - - 25 25 19 20 - - - -
87 16 17 17 18 27 27 27 30 - - - -
88 20 21 - - 20 21 23 23 - - - -
89 11 11 16 16 28 28 23 25 - - 16 16
90 13 14 17 16 34 35 20 22 16 17 20 19
91 12 13 - 15 20 20 25 28 - - 16 16
92 11 13 - - 18 18 31 33 - - 15 -
93 26 26 - - 34 34 33 38 17 18 19 19
94 21 22 19 19 15 15 33 35 - - - -
95 10 12 18 20 19 20 31 34 - - - -
96 23 23 26 27 35 35 28 30 15 18 18 19
97 10 12 - - 23 22 30 35 - - 18 17
98 12 13 - - 15 16 24 25 17 16 - -
99 17 17 - - 22 23 29 31 - - - -
100 14 14 - - 27 27 18 21 - - - 15
101 18 19 15 16 30 31 21 25 - - 16 17
102 17 18 - - 23 23 21 26 - - - -
103 11 13 15 - 15 15 27 31 - - 18 18
104 8 7 - - 22 23 16 20 - - - -
105 15 15 - - - - 20 26 - - - -
106 15 16 - - 15 15 20 25 - - - -
107 11 11 - - 16 16 20 21 - - - -
108 14 14 15 17 - - 25 31 - - 16 16
109 23 25 16 17 18 18 34 39 - - - -
110 15 16 18 17 - - 21 26 - - - -
111 18 18 19 19 - - 22 29 - - - -
112 14 15 - - - - 15 22 - - - -
113 11 11 - - - - - 20 15 16 - -
114 19 20 - - - - - 21 - - - -
115 24 23 - - 15 15 - - - 15 - -
116 11 10 - - - - 17 24 15 15 - -
117 14 14 - - - - - 24 - - 16 16
118 9 10 - - - - - 21 16 17 - -
119 12 12 - - - - 18 32 - - - -
120 15 16 18 18 - - 17 22 - - - -
121 16 15 - - - - - 25 - - - -
122 16 16 18 17 - - - - 18 19 - -
123 16 16 - - - - - 18 - - - -
124 22 22 - - - - 16 27 - - - -

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________

a3
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 22 47 18 30 62 92 52 52 38 34 19 -
25 25 73 17 16 63 108 56 51 18 26 26 15
26 22 35 - 17 58 104 47 56 26 29 19 16
27 16 37 22 21 52 90 59 61 24 30 19 17
28 23 50 18 23 72 109 60 51 26 40 27 25
29 19 39 29 26 84 110 76 74 33 39 - 19
30 36 53 19 27 64 86 55 51 22 38 27 22
31 30 54 19 29 64 98 51 61 23 26 25 18
32 27 47 19 17 49 68 51 49 30 30 24 20
33 21 33 20 21 69 98 59 70 27 32 22 19
34 19 37 - 18 54 84 59 60 22 26 27 24
35 18 37 18 - 72 92 39 49 26 29 17 16
36 18 28 18 17 50 69 55 53 20 24 18 -
37 18 39 19 22 53 77 42 49 30 31 20 18
38 20 33 20 18 60 88 45 40 28 32 20 23
39 17 29 21 22 69 83 43 47 21 23 24 19
40 20 38 17 24 48 64 42 51 20 22 22 18
41 24 32 26 28 39 61 48 55 25 29 23 23
42 23 33 22 23 58 67 49 48 22 23 18 18
43 29 37 - 18 44 63 50 47 19 24 24 22
44 27 43 17 18 62 85 45 52 28 26 18 17
45 23 38 15 19 49 66 54 48 - 15 23 22
46 17 36 16 - 62 75 36 44 19 22 23 20
47 15 20 - - 45 63 38 36 - - - -
48 15 34 19 20 42 47 40 40 - 15 17 17
49 20 32 - - 42 52 45 51 17 19 - -
50 19 30 23 26 50 59 40 42 24 33 16 -
51 16 27 16 16 38 45 49 43 - 20 15 -
52 20 30 - - 43 49 32 33 - 15 15 -
53 - 26 21 18 47 59 41 41 23 27 17 19
54 19 24 - - 46 58 30 30 30 30 - -
55 16 18 17 21 44 53 34 37 20 18 20 18
56 22 30 - - 38 48 48 46 25 21 16 15
57 23 31 15 - 37 47 31 37 17 19 17 19
58 - 21 18 21 46 54 27 30 28 28 19 15
59 - 21 18 22 31 38 34 34 - 16 20 16
60 - 20 - 15 40 47 37 37 21 21 15 -
61 16 24 15 - 48 58 27 33 22 22 - 19
62 15 26 21 22 46 51 32 35 18 18 - -
63 - 20 15 20 32 35 36 33 - 17 - -
64 16 23 - 16 42 49 37 37 - - - -
65 19 23 - - 34 38 45 43 - - - -
66 - 23 - - 42 47 21 24 23 26 - 15
67 - 19 15 16 33 36 29 37 - - - -
68 - 22 - 16 38 42 31 31 - 17 - -
69 15 20 - - 28 30 34 31 - - - -
70 19 22 17 16 29 32 39 40 17 18 18 -
71 - 18 18 17 23 28 29 30 16 15 - -
72 - 20 - 15 35 39 19 17 - - - -
73 - 16 22 21 33 37 34 32 24 24 - -
74 25 28 17 16 41 44 31 30 26 23 - -
75 - 16 - 17 30 33 30 31 - - - -
76 - 17 - - 25 28 25 25 - - - -
77 17 23 - - 32 33 32 32 - - - -
78 17 20 - 17 40 43 26 27 - 15 17 -
79 - 16 - - 22 26 22 23 - - - -
80 - - - - 21 23 31 33 - - - -
81 16 21 - - 31 32 23 23 - - - -
82 - - - 15 25 28 29 28 - 16 - -
83 15 19 - - 27 32 18 21 - - - -
84 17 22 - - 22 25 25 27 - - - -
85 15 17 - - 33 34 21 21 - - - -
86 - - - - 31 33 24 27 15 16 - -
87 - 18 - - 30 32 - - - - - -
88 - - - - 24 24 27 26 - - - -
89 - 17 - - 28 28 20 19 - - - -
90 - - - - 28 30 15 15 - - - -
91 - 15 - - 29 30 - 15 17 20 - -
92 - - 15 18 - 15 - - - - - -
93 - - - - 24 24 25 27 15 16 - -
94 - 15 - - 24 24 16 16 16 17 - -
95 - - - - 27 27 17 20 - - - -
96 16 18 - - 26 26 16 15 - - - -
97 - 16 - - 24 25 15 15 - - - -
98 - 17 - - 25 25 15 15 - - - -
99 16 20 - 16 28 28 21 23 - - - -
100 - - - - 24 25 16 16 - - - -
101 - - - - 21 22 22 22 15 17 - -
102 - - - - - - 17 16 - - - -
103 - - - - - - 22 22 - - - -
104 - 15 - - 30 30 19 20 18 18 - -
105 - - - 15 27 27 - - - - - -
106 - - - - 22 23 21 21 - - - -
107 - 15 - - 21 21 18 17 - 15 - -
108 - - - - 18 19 18 18 - - - -
109 - - - - 19 20 17 17 - - - -
110 - - - - 18 20 21 20 16 16 - -
111 - - - - 17 19 - - - - - -
112 - - - - - - - - - - - -
113 - - - - - 15 - 15 - - - -
114 - - - - 22 23 15 15 - - - -
115 - - - - 17 17 16 16 - - - -
116 - - - - - 16 - - - - - -
117 - - - - 15 15 - - - - - -
118 - - - - 22 23 - - - - - -
119 - - - - - - - - - - - -
120 - - - - 17 17 - - - - - -
121 - - - - - - - - - - - -
122 - - - - - - - - - - - -
123 - - - - - - - - - - - -
124 - - - - - - - - - - - -

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________

b1
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 - - 15 15 - - - 17 - - 18 18
25 - - - - 22 23 18 27 - - 20 21
26 - - - - 23 23 - 17 - 15 22 22
27 - - 16 15 18 18 27 32 - 21 15 22
28 24 17 - 17 15 17 18 19 - - - -
29 25 - - 15 - 15 16 16 - - - -
30 29 17 - - 18 17 15 17 - - - -
31 19 - - - 16 - - - - - - -
32 20 15 - 17 - - 18 23 - - - -
33 17 19 - - 15 22 38 27 - - 19 22
34 22 18 - - - - 23 17 - - 17 26
35 21 17 - - 19 20 30 31 - - 22 27
36 23 26 - - - - 27 29 - - 24 29
37 16 20 - - - - 34 30 - - 27 28
38 17 18 - - 18 17 - - 15 - 17 15
39 15 15 - - - 15 16 - - - 22 31
40 - 17 - - 17 16 20 - - - 19 24
41 29 26 - - - - - - 17 - 17 26
42 - - - 16 21 22 17 15 - - 18 26
43 - 15 17 - 17 18 15 - 18 18 25 27
44 - - - - 15 - - - - - - -
45 - - - - 17 - - - - - - -
46 - - - - - - - - - - - -
47 - 17 - - 19 19 - - - - - -
48 - - - - - - 22 21 - - - -
49 - - - - - - 16 16 - 15 - -
50 - - - - 17 16 15 15 - - - -
51 - - - - - - 23 26 16 16 15 -
52 - - - - - - 19 21 - - - -
53 - - 25 21 15 - 17 18 - - 16 15
54 - - - - 16 15 27 27 - - 19 24
55 - - 16 - - - 24 24 - - - -
56 - - - - - - 24 25 - - 17 16
57 - - 16 16 - 15 38 38 - - 24 23
58 16 15 - - - - - - 16 - - -
59 - - - 16 - - - 16 16 - - -
60 19 17 - - 25 26 - - 15 - - -
61 19 16 - 17 22 22 - - - - - 15
62 19 20 - - - - 24 24 20 - - 15
63 17 17 15 15 - - 19 21 15 - - -
64 - 16 - - 19 18 20 19 21 16 - -
65 - - - - 19 19 23 24 - - - -
66 - - - - 17 16 18 18 - - - -
67 19 16 - 17 - 15 19 19 - - - -
68 - - - - - - 23 24 - - - -
69 - - - - - - 15 16 - - - 16
70 - - 15 - - - 18 18 - - - -
71 - - 16 15 - - 26 26 - - - -
72 18 21 - - - - 29 30 - - - -
73 - - - - - - 21 21 - - - -
74 19 21 - - - - 22 22 - - 15 15
75 - - - - - - - - - - 16 16
76 24 22 - - - - 19 19 - - - -
77 - - - - - - - - - - - -
78 20 19 - - - - 17 17 - - - -
79 20 19 - - - - 22 22 - - 16 18
80 - - - - - - 19 18 - - - -
81 - 17 - - - - 19 19 - - - -
82 - 16 - - - - 15 15 15 - - -
83 - - - - - - 16 17 - - 18 16
84 17 18 18 19 - - 22 22 - 17 18 20
85 - - 16 17 - - 18 17 - - 16 17
86 - - - - - - 19 19 - - - -
87 - - 15 16 - - 19 19 21 21 - -
88 - - - 17 - - 20 19 - - - 15
89 - - - 17 17 17 26 27 - - 16 -
90 - - - - 15 - 19 19 - - - -
91 - - - 16 15 15 24 25 - - - -
92 - 15 17 18 21 22 21 21 - - - -
93 15 - 17 21 - - 18 19 - - - -
94 - - 15 15 - - 15 16 - 15 - 15
95 - - - - 19 19 25 25 15 16 - -
96 - - 17 16 21 21 28 28 - - 17 19
97 - - - - 15 15 22 25 - - - -
98 16 16 - - 20 20 28 28 - - - -
99 - - - - 20 20 24 27 - - - -
100 - - - - 18 19 16 17 - - - -
101 - - - - - - 25 26 - - - -
102 15 - - - - - 22 24 - - - -
103 - - - - 17 17 20 20 - - - -
104 - - - - - - 20 21 - - - -
105 - - - - 15 15 16 17 - - - -
106 - - - - 16 17 26 27 - - - -
107 - - - - - - 24 24 - - - -
108 - - - - 17 18 18 19 - - - -
109 - - - - 15 17 19 19 - - - -
110 - - - - - - - - - - - -
111 - - - - - - 15 15 - - - -
112 - - - - - - 17 18 - - - -
113 - - - - - - - - - - - -
114 - - - - - - - - - - - -
115 - - - - - - - - - - - -
116 - - - - - - - - - - - -
117 - - - - - - - - - - - -
118 - - - - - - - - - - - -
119 - - - - - - - - - - - -
120 - - - - - - - - - - - -
121 - - - - - - - - - - - -
122 - - - - - - 16 16 - - - -
123 - - - - - - 16 16 - - - -
124 - - - - - - - - - - - -

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________

b47
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 60 83 53 61 129 158 141 131 36 41 43 41
25 55 73 69 75 107 137 157 148 41 44 48 51
26 53 74 45 50 105 128 142 148 36 43 50 53
27 58 77 44 44 136 150 143 148 35 44 38 39
28 50 79 43 56 119 137 111 115 37 48 42 52
29 57 76 55 59 102 127 127 120 36 35 30 34
30 59 79 59 60 110 123 137 125 26 26 39 41
31 57 67 55 55 119 142 116 119 39 44 39 46
32 58 83 51 56 109 119 109 115 40 44 35 37
33 58 69 60 61 121 133 131 137 34 38 42 41
34 42 58 50 56 93 100 105 106 36 40 35 43
35 43 61 47 52 97 106 101 106 33 28 32 33
36 59 70 48 50 111 125 104 106 27 29 31 32
37 49 61 48 51 105 111 125 117 40 44 31 42
38 56 69 57 63 84 98 81 82 37 35 46 45
39 51 59 28 43 102 111 118 123 31 37 39 41
40 41 46 60 59 103 110 106 102 17 26 38 39
41 41 48 46 44 89 103 93 91 38 37 30 32
42 42 46 39 45 90 107 68 70 28 33 22 25
43 44 55 39 45 82 91 95 90 24 31 36 38
44 58 65 43 47 88 98 83 83 - 16 27 26
45 41 52 45 46 67 81 83 79 32 35 26 22
46 43 53 36 35 100 105 92 90 36 36 30 36
47 38 38 38 34 65 70 81 86 32 35 31 32
48 35 45 36 39 66 68 91 91 29 27 29 35
49 43 55 36 39 86 92 78 79 25 21 34 37
50 49 58 33 43 74 86 87 89 26 22 24 24
51 43 50 41 50 82 87 89 86 30 33 46 47
52 39 47 40 42 86 94 94 93 29 32 30 35
53 38 51 41 42 73 76 72 68 21 25 21 27
54 49 53 29 29 87 85 56 55 32 33 25 30
55 46 52 36 42 79 85 86 87 35 32 25 27
56 49 61 49 54 90 95 73 71 25 33 30 28
57 36 46 36 38 75 83 80 79 26 29 28 26
58 26 33 35 33 81 87 83 79 22 26 29 33
59 31 39 30 31 61 65 79 76 26 25 29 32
60 33 37 27 31 61 67 56 56 24 23 28 29
61 40 45 33 35 67 74 69 69 29 31 25 27
62 32 39 28 26 88 93 73 73 23 23 27 33
63 23 24 28 25 55 62 67 67 26 21 22 19
64 29 38 26 24 43 48 71 70 26 24 34 36
65 39 42 30 29 52 54 58 60 21 23 15 20
66 19 26 22 22 52 57 66 62 18 18 31 39
67 39 42 30 31 66 69 57 56 19 20 27 33
68 29 32 31 28 58 60 60 63 17 18 22 31
69 26 31 20 22 55 57 70 68 18 18 26 30
70 32 38 25 22 55 56 52 50 23 24 29 29
71 33 35 32 35 40 41 53 51 - 16 21 22
72 33 35 22 21 55 56 58 59 18 21 22 20
73 34 35 32 28 43 47 45 47 25 24 24 28
74 30 34 33 30 45 48 56 59 21 27 16 19
75 33 36 24 25 52 54 46 46 21 19 22 20
76 27 29 35 34 43 44 42 42 - 17 18 17
77 31 32 21 19 47 50 55 51 17 19 22 25
78 33 36 37 34 41 44 53 51 19 17 28 33
79 24 26 27 23 43 45 55 53 20 20 29 30
80 36 38 15 16 54 53 44 41 17 19 25 25
81 38 40 18 18 53 54 37 37 24 25 18 19
82 20 21 22 26 40 41 54 53 16 15 19 21
83 25 26 24 25 29 30 39 37 15 15 26 23
84 26 30 32 30 36 37 47 45 - 15 22 22
85 22 24 20 21 40 41 45 45 28 27 21 26
86 27 27 24 27 46 48 43 43 18 19 20 22
87 26 27 28 31 53 55 42 41 15 15 16 20
88 27 25 19 17 40 41 50 48 - - 20 21
89 27 27 24 25 41 42 34 34 16 - 15 15
90 33 33 16 15 55 58 41 40 15 - - 16
91 25 29 17 18 50 50 29 29 15 15 - 16
92 26 26 18 20 36 37 47 48 21 21 - 15
93 27 28 25 22 31 32 55 54 - - 21 25
94 32 31 26 26 52 53 31 31 21 24 16 19
95 24 25 22 25 41 42 37 37 - 15 15 17
96 32 35 23 26 42 43 43 43 16 19 - 15
97 35 38 26 27 48 49 45 45 18 16 23 23
98 26 26 22 21 51 51 35 36 28 29 20 21
99 29 29 18 18 44 44 36 37 16 15 17 16
100 26 29 25 25 53 54 42 43 19 18 16 17
101 26 27 23 26 37 38 36 36 17 19 17 17
102 24 25 22 22 40 41 37 38 21 22 19 18
103 26 28 19 18 43 44 41 40 - - 19 18
104 30 32 21 19 40 40 34 34 15 - 18 20
105 24 27 31 29 38 38 45 44 - - 24 25
106 26 27 19 21 41 41 46 47 17 17 18 20
107 15 17 23 24 31 31 36 35 18 16 - -
108 22 25 18 18 41 41 32 31 - - 21 21
109 18 18 - - 39 40 32 32 - - 20 21
110 21 21 25 26 38 38 42 42 - - 15 15
111 26 27 21 18 38 39 36 36 - - 16 17
112 - - 21 21 35 35 37 36 15 17 19 19
113 18 20 22 22 37 38 31 30 - - - 15
114 22 22 24 24 27 27 37 37 - - - -
115 23 23 20 21 29 30 26 26 - - - -
116 20 20 26 27 27 28 29 30 17 17 - -
117 16 16 25 25 33 34 36 36 - - 15 16
118 17 19 20 20 31 31 31 30 - - - -
119 17 17 17 17 26 26 39 39 - - 17 19
120 - - - - 25 25 33 32 - - 15 -
121 17 19 19 19 38 38 43 44 - - 15 18
122 20 21 - - 34 35 32 32 - - - -
123 18 17 16 18 28 29 30 29 - - 17 16
124 15 16 22 22 25 25 34 34 - - - -

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________

c1
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 69 85 120 122 211 248 240 247 121 129 63 78
25 69 83 88 102 244 262 192 211 106 117 75 94
26 80 91 81 86 243 281 227 232 123 133 70 76
27 84 101 102 114 216 243 205 231 90 104 77 80
28 137 165 100 94 220 251 158 154 91 108 111 125
29 121 153 97 102 205 240 139 153 97 113 114 123
30 109 141 103 122 203 230 159 167 89 84 114 121
31 125 139 91 99 187 200 154 168 89 87 114 123
32 117 140 103 102 190 216 154 167 82 84 117 120
33 97 117 107 103 200 230 177 178 87 88 98 99
34 103 122 99 112 211 235 188 205 91 100 88 97
35 89 111 98 113 202 231 166 170 85 95 77 87
36 102 118 112 119 190 206 204 211 85 99 86 89
37 94 110 92 103 204 214 203 221 84 84 86 88
38 149 160 107 117 148 153 262 269 111 111 98 98
39 125 140 87 91 166 186 221 222 93 105 104 115
40 128 157 108 118 156 181 239 248 109 114 108 120
41 122 146 86 108 157 180 257 267 97 96 99 107
42 110 138 88 93 182 190 224 238 80 85 110 116
43 136 150 84 86 158 161 216 233 70 83 118 118
44 95 108 62 66 182 206 147 151 86 90 90 97
45 92 104 72 73 187 199 158 162 85 92 81 92
46 92 100 65 83 183 195 139 143 96 97 89 89
47 89 106 78 85 184 204 173 177 91 95 86 105
48 109 118 71 78 202 211 138 149 74 84 83 92
49 91 103 62 76 176 194 139 152 74 82 78 85
50 96 118 76 69 178 193 138 143 87 96 82 77
51 88 96 89 96 161 167 164 172 65 70 77 84
52 69 77 79 96 141 156 161 168 70 67 62 72
53 92 100 109 104 117 127 135 148 64 64 79 78
54 79 89 90 100 143 147 147 152 56 61 92 83
55 92 96 103 108 144 149 171 167 53 63 86 77
56 82 94 86 97 152 159 134 129 71 73 82 90
57 81 89 84 91 137 146 128 135 61 66 76 80
58 76 84 86 89 132 142 151 155 66 67 47 46
59 64 73 64 71 116 128 172 169 83 84 56 61
60 69 76 73 69 136 141 159 165 89 84 61 64
61 77 92 76 81 136 143 169 170 73 80 67 72
62 58 61 70 69 142 147 149 154 77 74 50 51
63 64 65 69 80 116 126 153 160 74 72 56 54
64 48 63 66 72 124 130 140 145 76 76 43 39
65 58 61 69 69 152 156 159 158 77 82 48 48
66 86 95 75 84 171 181 133 133 61 69 85 86
67 77 83 79 81 166 167 172 170 55 50 81 87
68 76 85 98 103 163 172 131 130 65 74 74 81
69 90 84 78 88 159 161 130 138 67 76 70 66
70 89 100 79 91 156 164 121 124 73 68 55 64
71 82 88 97 94 160 160 120 125 60 62 75 80
72 71 78 84 86 153 155 124 132 63 67 79 86
73 70 75 84 94 146 148 137 139 51 49 57 65
74 71 73 70 85 123 127 134 138 59 54 83 84
75 57 65 55 61 137 140 116 121 48 51 69 75
76 67 72 72 68 133 135 126 124 51 56 72 76
77 53 57 69 76 122 132 102 102 48 57 58 59
78 50 55 71 71 121 127 104 109 60 64 53 60
79 62 65 83 84 111 114 92 93 52 58 58 61
80 58 65 63 68 131 132 114 115 53 57 80 76
81 60 65 68 73 130 133 120 120 59 63 62 62
82 65 63 74 71 129 131 91 94 58 62 78 79
83 68 72 69 76 131 135 117 114 62 59 58 57
84 59 62 58 58 117 123 113 115 65 67 59 63
85 76 79 61 66 117 114 126 128 73 74 65 69
86 84 90 72 75 122 126 94 93 64 66 60 63
87 98 102 42 42 136 138 105 106 65 67 58 63
88 80 80 38 40 131 134 117 119 61 63 61 60
89 72 72 54 55 116 119 118 118 67 62 48 49
90 78 78 47 49 132 137 99 100 52 56 55 61
91 70 73 64 66 119 122 117 117 54 56 60 65
92 73 78 67 71 147 150 118 121 57 61 53 57
93 56 61 60 61 120 123 112 111 57 55 57 58
94 74 75 60 57 124 127 109 109 57 63 61 66
95 68 72 47 48 146 146 112 111 70 73 42 42
96 70 71 37 38 129 131 101 104 60 61 49 54
97 62 68 48 47 89 92 92 92 60 62 59 58
98 65 65 63 62 119 119 116 116 47 50 47 47
99 73 72 58 61 128 129 111 110 44 48 58 56
100 56 62 52 55 106 105 100 99 56 58 57 59
101 59 62 57 60 96 97 100 101 46 52 56 61
102 82 83 60 67 98 100 91 90 48 48 44 42
103 61 58 71 74 112 114 82 81 49 54 48 49
104 71 75 57 60 94 92 90 92 42 40 58 60
105 63 68 59 59 103 103 82 82 54 59 52 50
106 61 65 49 48 104 105 87 88 46 48 50 50
107 55 57 48 47 104 104 90 87 45 48 49 52
108 52 55 50 58 95 95 88 89 48 49 47 47
109 65 65 67 68 111 111 74 75 57 59 56 60
110 61 62 65 69 72 74 93 94 47 47 45 48
111 55 59 41 48 81 81 85 87 46 51 50 53
112 50 53 49 53 84 83 80 81 56 55 52 52
113 49 47 44 46 84 85 65 64 44 44 39 37
114 54 58 51 53 79 78 80 80 32 34 52 51
115 53 54 48 55 87 89 74 74 41 41 48 48
116 51 53 47 50 81 80 75 77 36 38 52 54
117 51 50 49 47 78 80 74 76 45 46 54 51
118 32 35 51 55 75 76 83 85 42 44 43 43
119 41 42 38 38 87 88 80 81 40 40 45 46
120 50 52 36 36 95 95 72 72 27 28 52 54
121 43 45 55 56 76 77 76 76 37 36 45 44
122 44 44 50 54 74 76 69 70 45 46 43 43
123 48 47 39 40 75 75 67 69 44 44 48 51
124 43 44 48 55 84 85 70 71 34 32 57 60

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________

c2
N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S

24 69 80 52 57 137 148 128 132 43 47 44 46
25 58 82 52 52 120 134 110 125 36 37 45 55
26 68 76 59 61 137 152 125 129 41 39 49 46
27 59 79 64 69 115 135 132 136 43 42 34 39
28 51 65 52 56 106 123 114 128 39 43 38 40
29 52 64 57 51 86 102 95 103 34 37 46 48
30 59 67 39 40 114 136 115 115 38 38 43 50
31 58 71 51 53 107 119 88 96 44 37 31 33
32 58 57 37 43 108 115 106 108 34 28 30 38
33 56 67 46 48 116 125 105 111 31 31 43 43
34 53 58 67 58 92 104 98 97 38 42 37 36
35 43 56 49 48 88 107 87 90 29 29 30 35
36 37 52 50 46 103 112 95 102 31 30 38 40
37 36 45 44 43 96 105 98 97 34 35 38 44
38 50 62 40 36 96 100 80 83 15 19 38 42
39 56 62 49 49 86 96 86 90 41 36 47 44
40 47 50 41 45 86 94 89 90 35 35 35 41
41 40 47 42 39 87 94 86 90 31 29 37 36
42 44 49 46 48 81 91 78 82 29 28 30 33
43 46 51 37 36 75 81 88 85 24 23 32 27
44 51 50 41 43 72 73 66 68 33 35 31 33
45 41 44 43 32 76 77 71 78 31 28 27 30
46 33 40 38 38 83 92 66 72 28 31 32 35
47 37 43 34 34 78 89 72 72 37 36 36 35
48 39 44 42 37 73 80 72 74 33 31 43 38
49 32 42 29 28 78 80 47 45 27 24 29 26
50 34 38 31 28 55 59 65 64 33 25 29 33
51 33 37 40 38 74 83 79 81 23 22 29 29
52 49 52 39 36 65 73 76 83 24 23 25 29
53 36 41 30 30 74 81 59 61 28 27 24 18
54 38 35 29 26 68 73 60 61 17 20 17 22
55 25 29 31 36 75 79 68 66 22 23 29 32
56 32 36 27 27 63 66 51 53 18 17 30 36
57 30 41 24 28 59 63 52 53 23 17 27 25
58 36 41 27 28 73 73 56 58 21 26 19 22
59 39 42 30 25 67 74 68 69 20 25 16 21
60 30 36 28 28 72 75 56 54 22 21 22 26
61 35 38 31 32 53 54 62 64 30 30 31 31
62 28 36 32 33 56 57 52 54 30 27 23 27
63 26 27 31 30 51 53 61 63 22 22 23 24
64 37 38 38 40 48 52 60 63 22 22 22 22
65 28 33 39 40 50 48 54 55 - - 16 19
66 38 42 27 25 52 55 47 48 21 18 29 31
67 33 40 34 33 57 60 60 64 22 22 27 28
68 30 33 37 33 51 52 56 54 27 27 25 25
69 23 25 38 37 54 53 44 47 19 20 26 27
70 27 28 34 31 47 47 55 54 20 22 15 -
71 - 16 32 35 47 50 66 69 18 24 18 15
72 35 38 26 27 40 44 45 45 22 20 21 23
73 27 30 27 28 46 48 47 45 24 26 26 27
74 32 35 27 28 48 49 49 47 19 20 27 29
75 29 32 31 31 54 58 55 54 15 16 24 21
76 35 36 26 26 44 44 44 43 17 19 19 17
77 24 27 20 19 47 51 48 46 20 19 20 21
78 19 24 25 25 57 60 47 49 - 15 23 22
79 22 24 26 25 39 40 44 43 16 16 17 15
80 31 34 27 29 30 33 45 46 21 26 28 27
81 21 23 25 24 50 54 37 38 16 16 17 18
82 30 33 26 24 41 42 37 37 - 16 15 15
83 23 25 24 26 36 37 41 39 - - 15 -
84 19 21 23 21 49 51 42 42 17 19 18 19
85 19 21 18 15 39 42 32 32 18 19 20 20
86 15 16 19 19 39 40 47 48 23 20 16 15
87 25 24 16 15 41 44 44 44 19 20 18 21
88 28 30 17 17 49 51 36 36 17 17 21 21
89 26 29 26 26 42 42 38 39 16 16 16 21
90 27 29 20 19 44 43 22 24 26 24 - -
91 28 28 24 22 42 43 33 32 - - 19 21
92 21 22 - - 35 36 44 43 - - 19 21
93 16 17 20 17 32 32 30 30 16 - - -
94 31 34 23 24 38 39 43 43 - - 18 21
95 20 21 20 20 43 43 39 40 19 18 19 16
96 21 23 23 22 33 33 25 24 - - - -
97 22 21 - - 35 37 36 34 - - - -
98 19 18 26 25 34 34 27 26 - - - -
99 18 20 20 20 38 37 35 35 15 16 18 19
100 17 16 17 17 29 29 35 34 16 17 21 21
101 - - 15 - 34 35 37 35 16 17 15 15
102 17 18 - - 29 30 34 31 - - 18 19
103 19 19 20 21 35 36 35 36 - - 18 19
104 21 20 19 20 29 31 38 37 - - 17 20
105 20 21 16 - 39 40 33 33 - - 16 16
106 17 17 22 23 29 29 34 34 - - - -
107 22 22 22 21 43 44 27 27 - - - -
108 18 18 17 17 30 31 32 32 - - - -
109 21 20 15 - 28 29 33 32 22 20 - -
110 17 18 18 18 28 27 35 34 - - - 15
111 - - - - 32 32 24 22 - - - -
112 21 21 16 16 31 31 33 34 - - 20 20
113 17 17 18 17 26 26 39 39 - - - -
114 - - 16 16 23 22 27 28 15 - 20 19
115 19 18 - - 35 36 32 33 - - 16 16
116 19 22 - - 32 32 20 20 - - - -
117 15 16 19 20 21 21 32 32 - - 17 18
118 20 20 18 17 25 25 31 31 - - 17 17
119 - - - - 27 28 28 28 - - 16 16
120 22 26 15 15 28 29 27 28 - - - -
121 18 20 15 - 33 34 23 23 - - - -
122 15 18 16 15 25 25 26 26 - - - -
123 17 20 - - 29 29 30 30 - - 19 20
124 - - 15 - 24 24 18 18 - - - -

N N R R N N R R N N R R
1 1 1 1 2 2 2 2 3 3 3 3
C S C S C S C S C S C S
____________________________________________________________


Date Subject Author
11/21/12
Read Interpretation of coefficients in multiple regressions which model
linear dependence on an IV
Halitsky
11/21/12
Read The problematic regression is actually ln(c) on ( ln(u), ln(u^2) ),
not c on (u, u^2)
Halitsky
11/22/12
Read Re: The problematic regression is actually ln(c) on ( ln(u), ln(u^2)
), not c on (u, u^2)
Ray Koopman
11/22/12
Read Off-line Zip File with one Summ File and 12 Detl files for lnc on (lnu,(lnu)^2)
Halitsky
11/23/12
Read Re: Off-line Zip File with one Summ File and 12 Detl files for lnc on (lnu,(lnu)^2)
Ray Koopman
11/23/12
Read Re: Off-line Zip File with one Summ File and 12 Detl files for lnc on (lnu,(lnu)^2)
Halitsky
11/23/12
Read Complete "a1_N_1_S" zipfile with results from all 3 new regressions
Halitsky
11/24/12
Read Re: Complete "a1_N_1_S" zipfile with results from all 3 new regressions
Ray Koopman
11/24/12
Read Re: Complete "a1_N_1_S" zipfile with results from all 3 new regressions
Halitsky
11/24/12
Read You now have N_1_S, N_2_S, and N_3_S files for all folds
Halitsky
11/25/12
Read As per your suggestion in the other thread, scaled e on scaled u, c, L
Halitsky
11/26/12
Read Re: As per your suggestion in the other thread, scaled e on scaled u,
c, L
Ray Koopman
11/26/12
Read Re: Interpretation of coefficients in multiple regressions which
model linear dependence on an IV
Ray Koopman
11/26/12
Read Them there is some neat algebraic mechanics !
Halitsky
11/27/12
Read Re: Them there is some neat algebraic mechanics !
Ray Koopman
11/27/12
Read OK – I think I’m set, at least till we get to c
on (e, u, u*e).
Halitsky
11/27/12
Read Re: OK – I think I’m set, at least till we get t
o c on (e, u, u*e).
Ray Koopman
11/28/12
Read Re: OK – I think I’m set, at least till we get t
o c on (e, u, u*e).
Ray Koopman
11/28/12
Read Thanks for your review of Tables I/II from previous analysis
Halitsky
11/27/12
Read Holy Cow! Look at your "average a1" slope regressed on Len Int
Halitsky
11/27/12
Read Re: Holy Cow! Look at your "average a1" slope regressed on Len Int
Ray Koopman
11/27/12
Read Re: Holy Cow! Look at your "average a1" slope regressed on Len Int
Halitsky
11/27/12
Read Re: Holy Cow! Look at your "average a1" slope regressed on Len Int
Ray Koopman
11/27/12
Read Here's how I did logs ...
Halitsky
11/27/12
Read Please note that $u = u in last post (the $ prefix is from PERL - sorry).
Halitsky
11/27/12
Read Re: Here's how I did logs ...
Ray Koopman
11/28/12
Read Average slopes and means of u' for c on (u',u'^2) WITHOUT logs
Halitsky
11/28/12
Read Results (!!) on average slopes and means for a1_N_1_C (complement
instead of core subset)
Halitsky
11/28/12
Read Re: Results (!!) on average slopes and means for a1_N_1_C (complement
instead of core subset)
Ray Koopman
11/28/12
Read Finally! Pay-off for all that work I did with the "A" matrix returned
by Ivor Welch's module!
Halitsky
11/29/12
Read Average Slope SEs for a1_N_1_S and a1_N_1_C (and some questions
regarding them ...)
Halitsky
11/30/12
Read Re: Average Slope SEs for a1_N_1_S and a1_N_1_C (and some questions
regarding them ...)
Ray Koopman
12/2/12
Read Re: Average Slope SEs for a1_N_1_S and a1_N_1_C (and some questions
regarding them ...)
Ray Koopman
12/2/12
Read Re: Average Slope SEs for a1_N_1_S and a1_N_1_C (and some questions
regarding them ...)
Ray Koopman
12/2/12
Read Glad you brought up “singleton” length intervals
... been thinkin’ on ‘em also ...
Halitsky
12/2/12
Read Re: Glad you brought up “singleton” length inter
vals ... been thinkin’ on ‘em also ...
Ray Koopman
12/2/12
Read It's still 24...124 - don't know why I bothered to say "roughly
25...125" instead of "exactly "24...124"
Halitsky
12/2/12
Read You should probably clear your data deck and start fresh with the two
csv's I just mentioned in the last email
Halitsky
12/2/12
Read Re: Glad you brought up “singleton” length inter
vals ... been thinkin’ on ‘em also ...
Halitsky
12/2/12
Read One last thought: definitions for the third regression (will save a
complete re-run if I incorporate them now) ...
Halitsky
12/3/12
Read Number of Bonferroni entries for each singleton length is still 72 (duh!)
Halitsky
11/30/12
Read En passant question: What if a plot of slope CI’s
is lousy, but splits the “m’s” perfectly?
Halitsky
11/30/12
Read Re: En passant question: What if a plot of slope CI
’s is lousy, but splits the “m’s” perfectly?
Ray Koopman
12/1/12
Read I’m glad the perfect m split legitimately suggests
a subset effect; here’s why.
Halitsky
12/1/12
Read Re: I’m glad the perfect m split legitimately sugg
ests a subset effect; here’s why.
Ray Koopman
12/1/12
Read Re: I’m glad the perfect m split legitimately sugg
ests a subset effect; here’s why.
Halitsky
12/1/12
Read Slope and intercept for R'uq in the above example ...
Halitsky
12/1/12
Read Bonferroni tables for p’s from new 2-ways for Auq
per fold and length interval
Halitsky
12/1/12
Read Nope! 24-entry Bonferroni tables for (a1,a3) and (b1,b47) do NOT
improve results for a3 nor b47
Halitsky
12/5/12
Read I'm VERY glad you'll know how to answer this "perms and combs"
question !
Halitsky
12/5/12
Read “L-H Het” Table for Average Slopes Auq, Aubu, Au
bqu
Halitsky
12/5/12
Read In "L-H Het table", L-H Het for N1 Aubu should be 4, NOT 2
Halitsky
12/5/12
Read Holy Moly, were you right about covariances for Rub and Rubq !!!!
Halitsky
12/5/12
Read Re: Holy Moly, were you right about covariances for Rub and Rubq !!!!
Ray Koopman
12/6/12
Read So do we need to "Bonferroni-correct" in this case
Halitsky
12/7/12
Read Re: So do we need to "Bonferroni-correct" in this case
Ray Koopman
12/7/12
Read Response to your last of 12/7 at 12:17am
Halitsky
12/7/12
Read Re: Response to your last of 12/7 at 12:17am
Ray Koopman
12/7/12
Read Thanks for the guidance on how to evaluate the contribution of u^2 in
the second model.
Halitsky
12/7/12
Read Please ignore my first question about "estimated standard errpr" in
my last post !!!! Sorry !
Halitsky
12/7/12
Read The u^2 coefficient in c on (e,u,u*e,u^2) does NOT distinguish among
the four subset x MoSS roll-ups
Halitsky
12/7/12
Read Sorry! Those were the SE's in my last post, not the t's !
Halitsky
12/7/12
Read SE's and p's for four subset x MoSS roll-ups of u*e coefficient in c
= (u,e,u*e)
Halitsky
12/7/12
Read Re: SE's and p's for four subset x MoSS roll-ups of u*e coefficient
in c = (u,e,u*e)
Ray Koopman
12/7/12
Read I'm sorry Ray - excitement (probably unwarranted) has disconnected my
brain from my fingers ...
Halitsky
12/7/12
Read Must we say S,N instead of N,S if we've said "Subset x MoSS" (not
MoSS x Subset) ???
Halitsky
12/7/12
Read Re: Must we say S,N instead of N,S if we've said "Subset x MoSS" (not
MoSS x Subset) ???
Ray Koopman
12/7/12
Read Response to your last
Halitsky
12/8/12
Read Re: Response to your last
Ray Koopman
12/8/12
Read Re: Response to your last
Ray Koopman
12/8/12
Read I think I understand; if so, then here’s what I ex
pect you’ll agree I should do next
Halitsky
12/9/12
Read Thanks so much for the sample picture you sent off-line
Halitsky
12/8/12
Read One other thing - because we're using "c-average", not "c-simple",
"c" is no longer a pure count
Halitsky
12/8/12
Read One other possibly worthwhile observation regarding the term u*e in
the regression c on (e,u,u^e,u^2)
Halitsky
12/8/12
Read Typo's of u^e for u*e in previous post.
Halitsky
12/9/12
Read Could I impose on you for four more ordered p “ref
erence plots”?
Halitsky
12/9/12
Read Have sent off-line a PDF of the four plots themselves graphed all together.
gimpeltf@hotmail.com
12/9/12
Read I'm getting the hang of the plotting now - see PDF SNa1_1_for_Rubq
sent offline
Halitsky
12/9/12
Read Am resending the last PDF sent off-line, since I've now learned how
to highlight the line of interest against the random backdrop.
Halitsky
12/10/12
Read Re: Am resending the last PDF sent off-line, since I've now learned
how to highlight the line of interest against the random backdrop.
Ray Koopman
12/10/12
Read 1) Just u*e and u^2(!!); 2) IOTs vs “proper” tes
ts
Halitsky
12/10/12
Read Re: 1) Just u*e and u^2(!!); 2) IOTs vs “proper”
tests
Ray Koopman
12/10/12
Read Response to your last re Q and p
Halitsky
12/10/12
Read Sorry! I meant set=2, not set =1 in last post ...
Halitsky
12/11/12
Read Re: Response to your last re Q and p
Ray Koopman
12/11/12
Read 1) yes - I am using abs(t); 2) subtraction from 1
Halitsky
12/10/12
Read Results of p's obtained by referring Q’s to the ch
i-square distribution.
Halitsky
12/11/12
Read Correction to harmless "thought-typo" in last post
Halitsky
12/11/12
Read Another way to bring the other folds in might be via investigation of
your average slopes and covar vis a vis "hetness"
Halitsky
12/11/12
Read Re: Results of p's obtained by referring Q’s to th
e chi-square distribution.
Ray Koopman
12/11/12
Read OK then, how ‘bout “hetness”? Are you amenabl
e to its further investigation?
Halitsky
12/12/12
Read Re: OK then, how ‘bout “hetness”? Are you amen
able to its further investigation?
Ray Koopman
12/12/12
Read I need to correct an apparent miscommunication regar
ding derivation of het H’s and L’s
Halitsky
12/13/12
Read Re: I need to correct an apparent miscommunication r
egarding derivation of het H’s and L’s
Ray Koopman
12/13/12
Read The SE's are in the zipped files but here they are for your
convenience ....
Halitsky
12/13/12
Read Re: The SE's are in the zipped files but here they are for your
convenience ....
Ray Koopman
12/13/12
Read Re your question about "linearity of SE’s in lengt
h"
Halitsky
12/14/12
Read Re: Re your question about "linearity of SE’s in l
ength"
Ray Koopman
12/14/12
Read Your question re features of (L,Aubqe) plots
Halitsky
12/13/12
Read I think I may have found something relevant to Aubqe
“het-ness” and heteroscedasticity
Halitsky
12/13/12
Read Re: I think I may have found something relevant to A
ubqe “het-ness” and heteroscedasticity
Ray Koopman
12/14/12
Read Re your questions about the plots sent off-line (and the underlying
data posted here 12/13 at 10:33am)
Halitsky
12/14/12
Read Re: Re your questions about the plots sent off-line (and the
underlying data posted here 12/13 at 10:33am)
Ray Koopman
12/14/12
Read Thanks for the terminological/methodological corrections, and also
for the ref to gnuplot.
Halitsky
12/14/12
Read Re: Thanks for the terminological/methodological corrections, and
also for the ref to gnuplot.
Ray Koopman
12/14/12
Read Response to your last of 12/14 at 227pm re terminology and methodology.
Halitsky
12/14/12
Read Re linearity of the Axxxx SE plots – hold on to yo
ur hat
Halitsky
12/14/12
Read Re: Re linearity of the Axxxx SE plots – hold on t
o your hat
Ray Koopman
12/14/12
Read Thanks for doing those two plots - yes - we agree on what we're seeing
Halitsky
12/14/12
Read Re: Thanks for doing those two plots - yes - we agree on what we're seeing
Ray Koopman
12/15/12
Read Re: Thanks for doing those two plots - yes - we agree on what we're seeing
Ray Koopman
12/15/12
Read Re plot of SEP against L
Halitsky
12/15/12
Read Effect of multiplying SE by sqrt(N), as per your post of 12/14 at 10:34pm
Halitsky
12/15/12
Read Re: Effect of multiplying SE by sqrt(N), as per your post of 12/14 at 10:34pm
Ray Koopman
12/14/12
Read One other general question regarding scaling to [0,1].
Halitsky
12/14/12
Read Re: One other general question regarding scaling to [0,1].
Ray Koopman
12/14/12
Read Sorry - I will be typographically more careful re Aubqe in the future.
Halitsky
12/1/12
Read Re: Interpretation of coefficients in multiple regressions which
model linear dependence on an IV
Ray Koopman
12/1/12
Read Thanks for elucidation of 2nd new regression.
Halitsky
12/1/12
Read Re: Interpretation of coefficients in multiple regressions which
model linear dependence on an IV
Ray Koopman
12/1/12
Read Roger corrected defs; also, will add new cov, just in case it's
needed later
Halitsky
12/2/12
Read Re: Interpretation of coefficients in multiple regressions which
model linear dependence on an IV
Ray Koopman
12/2/12
Read 1) thanks for the 3rd regression defs; 2) Yes - I see why the terms
aren't "symmetrical" in this case.
Halitsky
12/3/12
Read New copies of a1_N_1_C and a1_N_1_S with data for all three
regressions at each singleton length.
Halitsky
12/3/12
Read Since 3rd regression computation needs df = 5, am requiring 15
observations for any given length singleton in any cell
Halitsky
12/3/12
Read Have sent off-line all N_1 regression coefficient files and master N
per length index file for N1
Halitsky
12/3/12
Read Same as above post for f_N_2_ss
Halitsky
12/3/12
Read Same as above post for f_N_3_ss
Halitsky
12/3/12
Read Same as above post for f_R_1_ss
Halitsky
12/3/12
Read Same as above post for f_R_2_ss
Halitsky
12/3/12
Read Same as above post for f_R_3_ss
Halitsky
12/3/12
Read Re: Since 3rd regression computation needs df = 5, am requiring 15
observations for any given length singleton in any cell
Ray Koopman
12/4/12
Read Sparseness of b1 data ...
Halitsky
12/4/12
Read I realized I should clarify my 4-way b1 match table: it's AFTER
subtracting df of 3
Halitsky
12/4/12
Read Re: I realized I should clarify my 4-way b1 match table: it's AFTER
subtracting df of 3
Ray Koopman
12/4/12
Read No - the counts in the files themselves are all OK.
Halitsky
12/4/12
Read Re: Sparseness of b1 data ...
Ray Koopman
12/5/12
Read We cross posted, so I just saw your revised "counts" table after I
made my last two posts ...
Halitsky
12/4/12
Read Let me know if you're ready for some interesting data, or if you're
too busy analyzing
Halitsky
12/4/12
Read Re: Let me know if you're ready for some interesting data, or if
you're too busy analyzing
Ray Koopman
12/4/12
Read Please evaluate this "yield" table of method/subset avg slope 2-ways
per fold and len with p < .05
Halitsky
12/5/12
Read One other question about using Auq avg slope as a constant when
computing the other two regressions
Halitsky
12/5/12
Read Re: One other question about using Auq avg slope as a constant when
computing the other two regressions
Ray Koopman
12/5/12
Read Re: One other question about using Auq avg slope as a constant when
computing the other two regressions
Halitsky
12/4/12
Read Some of your counts apparently ARE off.
Halitsky
12/4/12
Read Sorry! those counts in my last post were for len 63 in b1 (forgot to
tell you the length!!!!)
Halitsky
12/4/12
Read Re: Since 3rd regression computation needs df = 5, am requiring 15
observations for any given length singleton in any cell
Ray Koopman

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