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Re: st: working with a vector and scalars
Here's a solution to my question about working with vectors and scalars. Thank you, Austin Nichols, for providing initial code and a hint about difficulty generating element-wise reciprocals.
I initially had a problem using the "placeXhr" variable in the -mean- command, because "placeXhr" is a string variable. That problem is solved by using both "place" and "hour" variables in -mean-.
The reliabilities in the sub-groups turned out to be very similar.
Cathy
----
*Calculate reliabilities for place/hour groups.
egen N = count(crowdindx), by(place hour)
gen nr=1/N
mean nr, over(place hour)
mat b=e(b)
mat N=b'
matrix rownames N = `e(over_labels)'
loneway crowdindx placeXhr
matrix sj = N * (r(sd_w) * r(sd_w))
local tau = r(sd_b) * r(sd_b)
matrix t = J(48,1,`tau')
matrix J = t,sj
matrix rownames J = `e(over_labels)'
matrix colnames J = tau sigma_nj
preserve
drop _all
svmat J, names(col)
tempfile mat
save `mat'
use `mat'
gen lambda_j = tau / (tau + sigma_nj)
restore
*End of reliability analysis.
On Mon, 9 Jun 2008, Cathy L. Antonakos wrote:
Date: Mon, 9 Jun 2008 08:52:07 -0400 (EDT)
From: Cathy L. Antonakos <[email protected]>
Reply-To: [email protected]
To: [email protected]
Subject: Re: st: working with a vector and scalars
You're right. The "d" in the equation should be "s" (sigma-squared). I can
get the reliability reported by -loneway- for the overall sample mean, but I
want the reliabilities for each group.
Yes, I think it would be easier in Mata, but I don't know how to do that.
When I ran the syntax you provided, the -mean- command gave an error:
. mean nr, over(placeXhr)
no observations
r(2000);
If I can figure out that error, I think the approach will work.
On Sun, 8 Jun 2008, Austin Nichols wrote:
Date: Sun, 8 Jun 2008 21:00:38 -0400
From: Austin Nichols <[email protected]>
Reply-To: [email protected]
To: [email protected]
Subject: Re: st: working with a vector and scalars
Cathy L. Antonakos <[email protected]>
I take it you don't want the reliability reported by -loneway-? Not
sure what you want from your description... but I don't think that
equation looks right, and I don't have the ref handy. Can you confirm
that t cancels out? Is your calculated s equiv to d in your formula?
I don't see where you've tried to calculate something and gotten an
error, but try:
egen N = count(crowdindx), by(placeXhr)
g nr=1/N
mean nr, over(placeXhr)
mat b=e(b)
mat N=b'
loneway crowdindx placeXhr
scalar t = r(sd_b) * r(sd_b)
scalar s = r(sd_w) * r(sd_w)
mat lambda = s*N
mat li lamdba
But if you need to calculate the element-wise reciprocal, it's easier in
Mata...
On Sun, Jun 8, 2008 at 8:23 PM, Cathy L. Antonakos <[email protected]>
wrote:
I am working with scalars and a vector to estimate sample mean reliability
by group, using a formula from Bryk & Raudenbush (1992) Hierarchical
Linear
Models:
lambda-j = t / [ t / (d /Nj)]
lambda-j is the reliability estimate for group j, t is between-group
variance, d is within-group variance, and Nj is the group N.
Nj is a vector. The other parameters (t, d) are scalars.
Here's what I tried using -matrix- and -scalar-. The vector comes from a
collapsed dataset. The scalars come from -loneway- using the original
(uncollapsed) dataset. I have no trouble producing the vector and scalars,
but can't figure out how to get them into the same matrix or file together
so I can calculate the reliability esimates.
Any help will be much appreciated.
Cathy Antonakos
--------------
. bys placeXhr: egen N = count(crowdindx)
. preserve
. collapse (max) N, by(placeXhr)
. mkmat N
. levelsof placeXhr, local(l)
. matrix rownames N = `l' . matrix list N
N[49,1]
N
2_10 2
2_11 81
2_12 150
2_13 340
2_14 138
2_15 82
2_16 102
2_17 119
2_18 288
2_19 160
2_8 48
2_9 265
3_10 166
3_11 71
3_12 63
3_13 25
3_14 53
3_15 68
3_16 44
3_17 61
3_18 33
3_19 35
3_8 36
3_9 16
6_10 33
6_11 69
6_12 82
6_13 30
6_14 87
6_15 90
6_16 90
6_17 92
6_18 63
6_19 79
6_8 86
6_9 41
9_10 57
9_11 135
9_12 113
9_13 83
9_14 152
9_15 168
9_16 160
9_17 151
9_18 97
9_19 147
9_8 216
9_9 166
9_9 190
. restore
. *create matrices from -loneway- parameter estimates.
. preserve
. loneway crowdindx placeXhr
One-way Analysis of Variance for crowdindx: Crowding Index (wtd. sum)
Number of obs = 5121
R-squared = 0.5384
Source SS df MS F Prob > F
-------------------------------------------------------------------------
Between placeXhr 682650.69 47 14524.483 125.87 0.0000
Within placeXhr 585364.53 5073 115.38824
-------------------------------------------------------------------------
Total 1268015.2 5120 247.65922
Intraclass Asy.
correlation S.E. [95% Conf. Interval]
------------------------------------------------
0.54152 0.06135 0.42126 0.66177
Estimated SD of placeXhr effect 11.67412
Estimated SD within placeXhr 10.74189
Est. reliability of a placeXhr mean 0.99206
(evaluated at n=105.73)
. return list
scalars:
r(lb) = .4212643949911408
r(ub) = .6617675540515819
r(se) = .0613539740927638
r(sd_w) = 10.74189173110937
r(sd_b) = 11.67412402231762
r(rho_t) = .9920556043556278
r(rho) = .5415159745213614
r(N) = 5121
. scalar t = r(sd_b) * r(sd_b) . scalar s = r(sd_w) * r(sd_w)
. restore
*
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*
* For searches and help try:
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* http://www.ats.ucla.edu/stat/stata/
*
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