Bartlett test

[ALKEBSEE RADWAN]

Hi everyone,
kindly I need to know the command of Bartlett test.
can someone help me please?
kindest,

[Joseph Coveney]

At the command line in Stata, type

search Bartlett

[Carlo Lazzaro]

Alkebee:
do you mean something along the following lines?

use "C:\Program Files\Stata16\ado\base\a\auto.dta"

. oneway price rep78, bonferroni

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      8360542.63      4   2090135.66      0.24     0.9174
 Within groups       568436416     64      8881819
------------------------------------------------------------------------
    Total            576796959     68   8482308.22

Bartlett's test for equal variances:  chi2(4) =  11.4252  Prob>chi2 = 0.022

                  Comparison of Price by Repair Record 1978
                                (Bonferroni)
Row Mean-|
Col Mean |          1          2          3          4
---------+--------------------------------------------
       2 |    1,403.1
         |      1.000
         |
       3 |    1,864.7    461.608
         |      1.000      1.000
         |
       4 |      1,507    103.875   -357.733
         |      1.000      1.000      1.000
         |
       5 |    1,348.5    -54.625   -516.233     -158.5
         |      1.000      1.000      1.000      1.000

.

Bartlett's test is covered in -oneway- entry, Stata .pdf manual.

[Joseph Coveney]

It is, indeed. You're not really limited to one-way ANOVA, though, if by "Bartlett test" the OP means NHST for heteroscedastic residuals. See below for a couple of alternative approaches that promise greater flexibility. (Despite them, I would be more inclined to examine residuals graphically for this.)

.ÿ
.ÿversionÿ16.1

.ÿ
.ÿlocalÿline_sizeÿ`c(linesize)'

.ÿsetÿlinesizeÿ78

.ÿ
.ÿclearÿ*

.ÿ
.ÿsetÿseedÿ`=strreverse("1581296")'

.ÿ
.ÿquietlyÿsysuseÿauto

.ÿsummarizeÿrep78,ÿmeanonly

.ÿquietlyÿreplaceÿrep78ÿ=ÿruniformint(r(min),ÿr(max))ÿifÿmi(rep78)

.ÿ
.ÿonewayÿpriceÿrep78

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿAnalysisÿofÿVariance
ÿÿÿÿSourceÿÿÿÿÿÿÿÿÿÿÿÿÿÿSSÿÿÿÿÿÿÿÿÿdfÿÿÿÿÿÿMSÿÿÿÿÿÿÿÿÿÿÿÿFÿÿÿÿÿProbÿ>ÿF
------------------------------------------------------------------------
Betweenÿgroupsÿÿÿÿÿÿ10722949.6ÿÿÿÿÿÿ4ÿÿÿ2680737.41ÿÿÿÿÿÿ0.30ÿÿÿÿÿ0.8794
ÿWithinÿgroupsÿÿÿÿÿÿÿ624342446ÿÿÿÿÿ69ÿÿÿ9048441.25
------------------------------------------------------------------------
ÿÿÿÿTotalÿÿÿÿÿÿÿÿÿÿÿÿ635065396ÿÿÿÿÿ73ÿÿÿ8699525.97

Bartlett'sÿtestÿforÿequalÿvariances:ÿÿchi2(4)ÿ=ÿÿ13.6115ÿÿProb>chi2ÿ=ÿ0.009

.ÿ
.ÿ/*ÿAnotherÿStataÿcommandÿtoÿconsider:ÿ*/
.ÿhetregressÿpriceÿi.rep78,ÿhet(i.rep78)ÿlrmodelÿnolog

HeteroskedasticÿlinearÿregressionÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿobsÿÿÿÿÿ=ÿÿÿÿÿÿÿÿÿ74
MLÿestimation
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿLRÿchi2(4)ÿÿÿÿÿÿÿÿ=ÿÿÿÿÿÿÿ3.88
Logÿlikelihoodÿ=ÿ-686.6222ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿÿÿÿÿÿÿ=ÿÿÿÿÿ0.4219

------------------------------------------------------------------------------
ÿÿÿÿÿÿÿpriceÿ|ÿÿÿÿÿÿCoef.ÿÿÿStd.ÿErr.ÿÿÿÿÿÿzÿÿÿÿP>|z|ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-------------+----------------------------------------------------------------
priceÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿÿ950.625ÿÿÿ1264.399ÿÿÿÿÿ0.75ÿÿÿ0.452ÿÿÿÿ-1527.551ÿÿÿÿ3428.801
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ1412.233ÿÿÿÿ773.193ÿÿÿÿÿ1.83ÿÿÿ0.068ÿÿÿÿ-103.1971ÿÿÿÿ2927.664
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿÿÿÿ858.5ÿÿÿ582.5866ÿÿÿÿÿ1.47ÿÿÿ0.141ÿÿÿÿ-283.3488ÿÿÿÿ2000.349
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿÿ1485.75ÿÿÿ995.6854ÿÿÿÿÿ1.49ÿÿÿ0.136ÿÿÿÿ-465.7576ÿÿÿÿ3437.258
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿÿÿÿÿ5017ÿÿÿ444.3134ÿÿÿÿ11.29ÿÿÿ0.000ÿÿÿÿÿ4146.162ÿÿÿÿ5887.838
-------------+----------------------------------------------------------------
lnsigma2ÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿ2.652991ÿÿÿ.8660254ÿÿÿÿÿ3.06ÿÿÿ0.002ÿÿÿÿÿ.9556122ÿÿÿÿ4.350369
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ2.722095ÿÿÿ.7527727ÿÿÿÿÿ3.62ÿÿÿ0.000ÿÿÿÿÿ1.246687ÿÿÿÿ4.197502
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿ1.279909ÿÿÿ.7745967ÿÿÿÿÿ1.65ÿÿÿ0.098ÿÿÿÿ-.2382722ÿÿÿÿ2.798091
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿ2.490359ÿÿÿ.8164966ÿÿÿÿÿ3.05ÿÿÿ0.002ÿÿÿÿÿ.8900556ÿÿÿÿ4.090663
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿ13.57935ÿÿÿ.7071068ÿÿÿÿ19.20ÿÿÿ0.000ÿÿÿÿÿ12.19345ÿÿÿÿ14.96526
------------------------------------------------------------------------------
LRÿtestÿofÿlnsigma2=0:ÿchi2(4)ÿ=ÿ16.92ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿ0.0020

.ÿ
.ÿ/*ÿYetÿsomethingÿelseÿtoÿthinkÿabout:ÿ*/
.ÿmixedÿpriceÿi.rep78,ÿresiduals(independent,ÿby(rep78))ÿ///
>ÿÿÿÿÿÿremlÿdfmethod(residual)ÿnolrtestÿnolog

Mixed-effectsÿREMLÿregressionÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿobsÿÿÿÿÿ=ÿÿÿÿÿÿÿÿÿ74
Groupÿvariable:ÿ_allÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿgroupsÿÿ=ÿÿÿÿÿÿÿÿÿÿ1

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿObsÿperÿgroup:
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿminÿ=ÿÿÿÿÿÿÿÿÿ74
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿavgÿ=ÿÿÿÿÿÿÿ74.0
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿmaxÿ=ÿÿÿÿÿÿÿÿÿ74
DFÿmethod:ÿResidualÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿDF:ÿÿÿÿÿÿÿÿÿÿÿminÿ=ÿÿÿÿÿÿ69.00
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿavgÿ=ÿÿÿÿÿÿ69.00
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿmaxÿ=ÿÿÿÿÿÿ69.00

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿF(4,ÿÿÿÿ69.00)ÿÿÿÿ=ÿÿÿÿÿÿÿ0.98
Logÿrestricted-likelihoodÿ=ÿ-649.53654ÿÿÿÿÿÿÿÿÿÿProbÿ>ÿFÿÿÿÿÿÿÿÿÿÿ=ÿÿÿÿÿ0.4255

------------------------------------------------------------------------------
ÿÿÿÿÿÿÿpriceÿ|ÿÿÿÿÿÿCoef.ÿÿÿStd.ÿErr.ÿÿÿÿÿÿtÿÿÿÿP>|t|ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-------------+----------------------------------------------------------------
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿÿ950.625ÿÿÿ1365.538ÿÿÿÿÿ0.70ÿÿÿ0.489ÿÿÿÿ-1773.548ÿÿÿÿ3674.798
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ1412.233ÿÿÿ823.0665ÿÿÿÿÿ1.72ÿÿÿ0.091ÿÿÿÿ-229.7394ÿÿÿÿ3054.206
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿÿÿÿ858.5ÿÿÿÿ642.405ÿÿÿÿÿ1.34ÿÿÿ0.186ÿÿÿÿ-423.0629ÿÿÿÿ2140.063
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿÿ1485.75ÿÿÿÿ1062.72ÿÿÿÿÿ1.40ÿÿÿ0.167ÿÿÿÿ-634.3176ÿÿÿÿ3605.818
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿÿÿÿÿ5017ÿÿÿ513.0478ÿÿÿÿÿ9.78ÿÿÿ0.000ÿÿÿÿÿ3993.498ÿÿÿÿ6040.502
------------------------------------------------------------------------------

------------------------------------------------------------------------------
ÿÿRandom-effectsÿParametersÿÿ|ÿÿÿEstimateÿÿÿStd.ÿErr.ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-----------------------------+------------------------------------------------
_all:ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ(empty)ÿ|
-----------------------------+------------------------------------------------
Residual:ÿIndependent,ÿÿÿÿÿÿÿ|
ÿÿÿÿbyÿrep78ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ1:ÿvar(e)ÿ|ÿÿÿÿ1052872ÿÿÿ859680.3ÿÿÿÿÿÿ212501.2ÿÿÿÿÿ5216629
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ2:ÿvar(e)ÿ|ÿÿÿ1.28e+07ÿÿÿÿ6848199ÿÿÿÿÿÿÿ4493905ÿÿÿÿ3.65e+07
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ3:ÿvar(e)ÿ|ÿÿÿ1.24e+07ÿÿÿÿ3263388ÿÿÿÿÿÿÿ7427049ÿÿÿÿ2.08e+07
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ4:ÿvar(e)ÿ|ÿÿÿÿ2989323ÿÿÿ969864.2ÿÿÿÿÿÿÿ1582729ÿÿÿÿÿ5645976
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ5:ÿvar(e)ÿ|ÿÿÿ1.04e+07ÿÿÿÿ4431956ÿÿÿÿÿÿÿ4506333ÿÿÿÿ2.40e+07
------------------------------------------------------------------------------

.ÿ//ÿWald
.ÿquietlyÿtestÿ_b[r_lns2ose:_cons]ÿ=ÿ0,ÿnotest

.ÿquietlyÿtestÿ_b[r_lns3ose:_cons]ÿ=ÿ0,ÿnotestÿaccumulate

.ÿquietlyÿtestÿ_b[r_lns4ose:_cons]ÿ=ÿ0,ÿnotestÿaccumulate

.ÿtestÿ_b[r_lns5ose:_cons]ÿ=ÿ0,ÿÿaccumulate

ÿ(ÿ1)ÿÿ[r_lns2ose]_consÿ=ÿ0
ÿ(ÿ2)ÿÿ[r_lns3ose]_consÿ=ÿ0
ÿ(ÿ3)ÿÿ[r_lns4ose]_consÿ=ÿ0
ÿ(ÿ4)ÿÿ[r_lns5ose]_consÿ=ÿ0

ÿÿÿÿÿÿÿÿÿÿÿchi2(ÿÿ4)ÿ=ÿÿÿ19.09
ÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿÿÿÿ0.0008

.ÿ//ÿLR
.ÿestimatesÿstoreÿFull

.ÿquietlyÿmixedÿpriceÿi.rep78,ÿremlÿdfmethod(residual)ÿnolrtestÿnolog

.ÿlrtestÿFull

Likelihood-ratioÿtestÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿLRÿchi2(4)ÿÿ=ÿÿÿÿÿ14.34
(Assumption:ÿ.ÿnestedÿinÿFull)ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿÿÿÿ0.0063

Note:ÿTheÿreportedÿdegreesÿofÿfreedomÿassumesÿtheÿnullÿhypothesisÿisÿnotÿon
ÿÿÿÿÿÿtheÿboundaryÿofÿtheÿparameterÿspace.ÿÿIfÿthisÿisÿnotÿtrue,ÿthenÿthe
ÿÿÿÿÿÿreportedÿtestÿisÿconservative.
Note:ÿLRÿtestsÿbasedÿonÿREMLÿareÿvalidÿonlyÿwhenÿtheÿfixed-effects
ÿÿÿÿÿÿspecificationÿisÿidenticalÿforÿbothÿmodels.

.ÿ
.ÿ/*ÿGivenÿthatÿyou'veÿgotÿit,ÿnowÿyouÿcanÿaccommodateÿitÿ.ÿ.ÿ.
>ÿÿÿÿ.ÿ.ÿ.ÿandÿwithÿsmall-sampleÿtestÿstatistics,ÿtoÿboot.ÿÿ*/
.ÿquietlyÿestimatesÿrestoreÿFull

.ÿcontrastÿrep78,ÿsmallÿÿÿ

Contrastsÿofÿmarginalÿlinearÿpredictions

Marginsÿÿÿÿÿÿ:ÿasbalanced

-----------------------------------------------------------
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|ÿÿÿÿÿÿÿÿÿdfÿÿÿÿÿÿÿÿddfÿÿÿÿÿÿÿÿÿÿÿFÿÿÿÿÿÿÿÿP>F
-------------+---------------------------------------------
priceÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|ÿÿÿÿÿÿÿÿÿÿ4ÿÿÿÿÿÿ69.00ÿÿÿÿÿÿÿÿ0.98ÿÿÿÿÿ0.4255
-----------------------------------------------------------

.ÿ
.ÿsetÿlinesizeÿ`line_size'

.ÿ
.ÿexit

endÿofÿdo-file


.

There are some user-written commands that are available for this, too, I think. (As well as for other things bearing the moniker.) That's why I recommended searching from within Stata.

[ALKEBSEE RADWAN]

Alkebee:
do you mean something along the following lines?

use "C:\Program Files\Stata16\ado\base\a\auto.dta"

. oneway price rep78, bonferroni

Analysis of Variance
Source SS df MS F Prob > F
------------------------------------------------------------------------
Between groups 8360542.63 4 2090135.66 0.24 0.9174
Within groups 568436416 64 8881819
------------------------------------------------------------------------
Total 576796959 68 8482308.22

Bartlett's test for equal variances: chi2(4) = 11.4252 Prob>chi2 = 0.022

Comparison of Price by Repair Record 1978
(Bonferroni)
Row Mean-|
Col Mean | 1 2 3 4
---------+--------------------------------------------
2 | 1,403.1
| 1.000
|
3 | 1,864.7 461.608
| 1.000 1.000
|
4 | 1,507 103.875 -357.733
| 1.000 1.000 1.000
|
5 | 1,348.5 -54.625 -516.233 -158.5
| 1.000 1.000 1.000 1.000

.

Bartlett's test is covered in -oneway- entry, Stata .pdf manual.

Yes it is.
but did you use command (Bartlett oneway price rep78, bonferroni) or what?

[ALKEBSEE RADWAN]

It is, indeed. You're not really limited to one-way ANOVA, though, if by "Bartlett test" the OP means NHST for heteroscedastic residuals. See below for a couple of alternative approaches that promise greater flexibility. (Despite them, I would be more inclined to examine residuals graphically for this.)

.ÿ
.ÿversionÿ16.1

.ÿ
.ÿlocalÿline_sizeÿ`c(linesize)'

.ÿsetÿlinesizeÿ78

.ÿ
.ÿclearÿ*

.ÿ
.ÿsetÿseedÿ`=strreverse("1581296")'

.ÿ
.ÿquietlyÿsysuseÿauto

.ÿsummarizeÿrep78,ÿmeanonly

.ÿquietlyÿreplaceÿrep78ÿ=ÿruniformint(r(min),ÿr(max))ÿifÿmi(rep78)

.ÿ
.ÿonewayÿpriceÿrep78

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿAnalysisÿofÿVariance
ÿÿÿÿSourceÿÿÿÿÿÿÿÿÿÿÿÿÿÿSSÿÿÿÿÿÿÿÿÿdfÿÿÿÿÿÿMSÿÿÿÿÿÿÿÿÿÿÿÿFÿÿÿÿÿProbÿ>ÿF
------------------------------------------------------------------------
Betweenÿgroupsÿÿÿÿÿÿ10722949.6ÿÿÿÿÿÿ4ÿÿÿ2680737.41ÿÿÿÿÿÿ0.30ÿÿÿÿÿ0.8794
ÿWithinÿgroupsÿÿÿÿÿÿÿ624342446ÿÿÿÿÿ69ÿÿÿ9048441.25
------------------------------------------------------------------------
ÿÿÿÿTotalÿÿÿÿÿÿÿÿÿÿÿÿ635065396ÿÿÿÿÿ73ÿÿÿ8699525.97

Bartlett'sÿtestÿforÿequalÿvariances:ÿÿchi2(4)ÿ=ÿÿ13.6115ÿÿProb>chi2ÿ=ÿ0.009

.ÿ
.ÿ/*ÿAnotherÿStataÿcommandÿtoÿconsider:ÿ*/
.ÿhetregressÿpriceÿi.rep78,ÿhet(i.rep78)ÿlrmodelÿnolog

HeteroskedasticÿlinearÿregressionÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿobsÿÿÿÿÿ=ÿÿÿÿÿÿÿÿÿ74
MLÿestimation
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿLRÿchi2(4)ÿÿÿÿÿÿÿÿ=ÿÿÿÿÿÿÿ3.88
Logÿlikelihoodÿ=ÿ-686.6222ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿÿÿÿÿÿÿ=ÿÿÿÿÿ0.4219

------------------------------------------------------------------------------
ÿÿÿÿÿÿÿpriceÿ|ÿÿÿÿÿÿCoef.ÿÿÿStd.ÿErr.ÿÿÿÿÿÿzÿÿÿÿP>|z|ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-------------+----------------------------------------------------------------
priceÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿÿ950.625ÿÿÿ1264.399ÿÿÿÿÿ0.75ÿÿÿ0.452ÿÿÿÿ-1527.551ÿÿÿÿ3428.801
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ1412.233ÿÿÿÿ773.193ÿÿÿÿÿ1.83ÿÿÿ0.068ÿÿÿÿ-103.1971ÿÿÿÿ2927.664
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿÿÿÿ858.5ÿÿÿ582.5866ÿÿÿÿÿ1.47ÿÿÿ0.141ÿÿÿÿ-283.3488ÿÿÿÿ2000.349
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿÿ1485.75ÿÿÿ995.6854ÿÿÿÿÿ1.49ÿÿÿ0.136ÿÿÿÿ-465.7576ÿÿÿÿ3437.258
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿÿÿÿÿ5017ÿÿÿ444.3134ÿÿÿÿ11.29ÿÿÿ0.000ÿÿÿÿÿ4146.162ÿÿÿÿ5887.838
-------------+----------------------------------------------------------------
lnsigma2ÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿ2.652991ÿÿÿ.8660254ÿÿÿÿÿ3.06ÿÿÿ0.002ÿÿÿÿÿ.9556122ÿÿÿÿ4.350369
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ2.722095ÿÿÿ.7527727ÿÿÿÿÿ3.62ÿÿÿ0.000ÿÿÿÿÿ1.246687ÿÿÿÿ4.197502
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿ1.279909ÿÿÿ.7745967ÿÿÿÿÿ1.65ÿÿÿ0.098ÿÿÿÿ-.2382722ÿÿÿÿ2.798091
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿ2.490359ÿÿÿ.8164966ÿÿÿÿÿ3.05ÿÿÿ0.002ÿÿÿÿÿ.8900556ÿÿÿÿ4.090663
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿ13.57935ÿÿÿ.7071068ÿÿÿÿ19.20ÿÿÿ0.000ÿÿÿÿÿ12.19345ÿÿÿÿ14.96526
------------------------------------------------------------------------------
LRÿtestÿofÿlnsigma2=0:ÿchi2(4)ÿ=ÿ16.92ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿ0.0020

.ÿ
.ÿ/*ÿYetÿsomethingÿelseÿtoÿthinkÿabout:ÿ*/
.ÿmixedÿpriceÿi.rep78,ÿresiduals(independent,ÿby(rep78))ÿ///
>ÿÿÿÿÿÿremlÿdfmethod(residual)ÿnolrtestÿnolog

Mixed-effectsÿREMLÿregressionÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿobsÿÿÿÿÿ=ÿÿÿÿÿÿÿÿÿ74
Groupÿvariable:ÿ_allÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿNumberÿofÿgroupsÿÿ=ÿÿÿÿÿÿÿÿÿÿ1

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿObsÿperÿgroup:
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿminÿ=ÿÿÿÿÿÿÿÿÿ74
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿavgÿ=ÿÿÿÿÿÿÿ74.0
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿmaxÿ=ÿÿÿÿÿÿÿÿÿ74
DFÿmethod:ÿResidualÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿDF:ÿÿÿÿÿÿÿÿÿÿÿminÿ=ÿÿÿÿÿÿ69.00
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿavgÿ=ÿÿÿÿÿÿ69.00
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿmaxÿ=ÿÿÿÿÿÿ69.00

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿF(4,ÿÿÿÿ69.00)ÿÿÿÿ=ÿÿÿÿÿÿÿ0.98
Logÿrestricted-likelihoodÿ=ÿ-649.53654ÿÿÿÿÿÿÿÿÿÿProbÿ>ÿFÿÿÿÿÿÿÿÿÿÿ=ÿÿÿÿÿ0.4255

------------------------------------------------------------------------------
ÿÿÿÿÿÿÿpriceÿ|ÿÿÿÿÿÿCoef.ÿÿÿStd.ÿErr.ÿÿÿÿÿÿtÿÿÿÿP>|t|ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-------------+----------------------------------------------------------------
ÿÿÿÿÿÿÿrep78ÿ|
ÿÿÿÿÿÿÿÿÿÿ2ÿÿ|ÿÿÿÿ950.625ÿÿÿ1365.538ÿÿÿÿÿ0.70ÿÿÿ0.489ÿÿÿÿ-1773.548ÿÿÿÿ3674.798
ÿÿÿÿÿÿÿÿÿÿ3ÿÿ|ÿÿÿ1412.233ÿÿÿ823.0665ÿÿÿÿÿ1.72ÿÿÿ0.091ÿÿÿÿ-229.7394ÿÿÿÿ3054.206
ÿÿÿÿÿÿÿÿÿÿ4ÿÿ|ÿÿÿÿÿÿ858.5ÿÿÿÿ642.405ÿÿÿÿÿ1.34ÿÿÿ0.186ÿÿÿÿ-423.0629ÿÿÿÿ2140.063
ÿÿÿÿÿÿÿÿÿÿ5ÿÿ|ÿÿÿÿ1485.75ÿÿÿÿ1062.72ÿÿÿÿÿ1.40ÿÿÿ0.167ÿÿÿÿ-634.3176ÿÿÿÿ3605.818
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿ_consÿ|ÿÿÿÿÿÿÿ5017ÿÿÿ513.0478ÿÿÿÿÿ9.78ÿÿÿ0.000ÿÿÿÿÿ3993.498ÿÿÿÿ6040.502
------------------------------------------------------------------------------

------------------------------------------------------------------------------
ÿÿRandom-effectsÿParametersÿÿ|ÿÿÿEstimateÿÿÿStd.ÿErr.ÿÿÿÿÿ[95%ÿConf.ÿInterval]
-----------------------------+------------------------------------------------
_all:ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ(empty)ÿ|
-----------------------------+------------------------------------------------
Residual:ÿIndependent,ÿÿÿÿÿÿÿ|
ÿÿÿÿbyÿrep78ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ1:ÿvar(e)ÿ|ÿÿÿÿ1052872ÿÿÿ859680.3ÿÿÿÿÿÿ212501.2ÿÿÿÿÿ5216629
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ2:ÿvar(e)ÿ|ÿÿÿ1.28e+07ÿÿÿÿ6848199ÿÿÿÿÿÿÿ4493905ÿÿÿÿ3.65e+07
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ3:ÿvar(e)ÿ|ÿÿÿ1.24e+07ÿÿÿÿ3263388ÿÿÿÿÿÿÿ7427049ÿÿÿÿ2.08e+07
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ4:ÿvar(e)ÿ|ÿÿÿÿ2989323ÿÿÿ969864.2ÿÿÿÿÿÿÿ1582729ÿÿÿÿÿ5645976
ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ5:ÿvar(e)ÿ|ÿÿÿ1.04e+07ÿÿÿÿ4431956ÿÿÿÿÿÿÿ4506333ÿÿÿÿ2.40e+07
------------------------------------------------------------------------------

.ÿ//ÿWald
.ÿquietlyÿtestÿ_b[r_lns2ose:_cons]ÿ=ÿ0,ÿnotest

.ÿquietlyÿtestÿ_b[r_lns3ose:_cons]ÿ=ÿ0,ÿnotestÿaccumulate

.ÿquietlyÿtestÿ_b[r_lns4ose:_cons]ÿ=ÿ0,ÿnotestÿaccumulate

.ÿtestÿ_b[r_lns5ose:_cons]ÿ=ÿ0,ÿÿaccumulate

ÿ(ÿ1)ÿÿ[r_lns2ose]_consÿ=ÿ0
ÿ(ÿ2)ÿÿ[r_lns3ose]_consÿ=ÿ0
ÿ(ÿ3)ÿÿ[r_lns4ose]_consÿ=ÿ0
ÿ(ÿ4)ÿÿ[r_lns5ose]_consÿ=ÿ0

ÿÿÿÿÿÿÿÿÿÿÿchi2(ÿÿ4)ÿ=ÿÿÿ19.09
ÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿÿÿÿ0.0008

.ÿ//ÿLR
.ÿestimatesÿstoreÿFull

.ÿquietlyÿmixedÿpriceÿi.rep78,ÿremlÿdfmethod(residual)ÿnolrtestÿnolog

.ÿlrtestÿFull

Likelihood-ratioÿtestÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿLRÿchi2(4)ÿÿ=ÿÿÿÿÿ14.34
(Assumption:ÿ.ÿnestedÿinÿFull)ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿProbÿ>ÿchi2ÿ=ÿÿÿÿ0.0063

Note:ÿTheÿreportedÿdegreesÿofÿfreedomÿassumesÿtheÿnullÿhypothesisÿisÿnotÿon
ÿÿÿÿÿÿtheÿboundaryÿofÿtheÿparameterÿspace.ÿÿIfÿthisÿisÿnotÿtrue,ÿthenÿthe
ÿÿÿÿÿÿreportedÿtestÿisÿconservative.
Note:ÿLRÿtestsÿbasedÿonÿREMLÿareÿvalidÿonlyÿwhenÿtheÿfixed-effects
ÿÿÿÿÿÿspecificationÿisÿidenticalÿforÿbothÿmodels.

.ÿ
.ÿ/*ÿGivenÿthatÿyou'veÿgotÿit,ÿnowÿyouÿcanÿaccommodateÿitÿ.ÿ.ÿ.
>ÿÿÿÿ.ÿ.ÿ.ÿandÿwithÿsmall-sampleÿtestÿstatistics,ÿtoÿboot.ÿÿ*/
.ÿquietlyÿestimatesÿrestoreÿFull

.ÿcontrastÿrep78,ÿsmallÿÿÿ

Contrastsÿofÿmarginalÿlinearÿpredictions

Marginsÿÿÿÿÿÿ:ÿasbalanced

-----------------------------------------------------------
ÿÿÿÿÿÿÿÿÿÿÿÿÿ|ÿÿÿÿÿÿÿÿÿdfÿÿÿÿÿÿÿÿddfÿÿÿÿÿÿÿÿÿÿÿFÿÿÿÿÿÿÿÿP>F
-------------+---------------------------------------------
priceÿÿÿÿÿÿÿÿ|
ÿÿÿÿÿÿÿrep78ÿ|ÿÿÿÿÿÿÿÿÿÿ4ÿÿÿÿÿÿ69.00ÿÿÿÿÿÿÿÿ0.98ÿÿÿÿÿ0.4255
-----------------------------------------------------------

.ÿ
.ÿsetÿlinesizeÿ`line_size'

.ÿ
.ÿexit

endÿofÿdo-file


.

There are some user-written commands that are available for this, too, I think. (As well as for other things bearing the moniker.) That's why I recommended searching from within Stata.

Thank you so much
I will try this if I faced issues I will ask you

[Carlo Lazzaro]

Alkebsee:
I typed:

oneway price rep78, bonferroni

.

That said, I would follow Joseph's excellent advice.

[ALKEBSEE RADWAN]

Alkebsee:
I typed:

oneway price rep78, bonferroni

.

That said, I would follow Joseph's excellent advice.

thank you sooooo much

[ALKEBSEE RADWAN]

one more thing is
how to explain or interpret the result?