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name: <unnamed>
log: /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/Randomization_Check.lo
> g
log type: text
opened on: 4 Nov 2021, 09:55:52
.
.
. use "${PATH_IN_DATA}/formatted_data_replication.dta", clear
. keep if round==1
(16,948 observations deleted)
.
.
. set scheme s1color_black_gray
.
. **********************************
. * Little program to convert matrix
. **********************************
.
. cap program drop convert
. program define convert, eclass
1. matrix list `1'
2. ereturn scalar N=.
3. ereturn matrix mean `1'
4. ereturn local estimates_title="p-values"
5. end
.
.
.
. * Generate variables specifallcy needed for balancing table
.
. egen ability_load_std_1=std(ability_load) if original_lab==1
(329 missing values generated)
. egen ability_task_std_1=std(ability_task) if original_lab==1
(329 missing values generated)
.
. egen ability_load_std=std(ability_load) if original_lab==0
(563 missing values generated)
. egen ability_task_std=std(ability_task) if original_lab==0
(563 missing values generated)
.
. replace ability_load_std=ability_load_std_1 if original_lab==1
(563 real changes made)
. replace ability_task_std=ability_task_std_1 if original_lab==1
(563 real changes made)
. drop ability_load_std_1 ability_task_std_1
.
. label var ability_task_std "Ability Decision Task (std.)"
. label var ability_load_std "Ability Background Task (std.)"
.
. bysort Treatment_Environment Treatment_Incentives: gen obs=_N
. label var obs "N"
.
.
. cap drop treatment_id
. egen treatment_id=group(Treatment_Environment Treatment_Incentives )
.
.
.
. * Write Balancing table; Different parts are appended after creating results via tabstat
.
. qui file open table_out using `"${PATH_OUT}/tableO_1.tex"', write replace
. file write table_out " \begin{tabular}{l*{13}{c}}" _n
. file write table_out "\toprule" _n
. file close table_out
.
. estimates clear
.
. bysort Treatment_Environment: eststo: estpost tabstat ability_load_std ability_task_std q_age q_gender economist perc_multitasking_2 perc_multitasking_1, by(Treatment_Incentives)
> nototal statistics(mean sd) columns(statistics) listwise
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Baseline}
Summary statistics: mean sd
for variables: ability_load_std ability_task_std q_age q_gender economist perc_multitasking_2 perc_multitasking_1
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
ability_l~td | -.0829961 1.051323
ability_ta~d | -.0271519 1.126178
q_age | 23.75524 5.527418
q_gender | .5804196 .4952249
economist | .1258741 .3328734
perc_multi~2 | 54.97203 18.9729
perc_multi~1 | 3.06993 .7750543
-------------+----------------------
20 |
ability_l~td | .1080402 .8993562
ability_ta~d | .0730191 1.024882
q_age | 23.74419 4.440576
q_gender | .5116279 .5057805
economist | .1162791 .324353
perc_multi~2 | 50.44186 19.22462
perc_multi~1 | 3.27907 .7661152
-------------+----------------------
40 |
ability_l~td | .0771499 1.191024
ability_ta~d | .2113969 .7026106
q_age | 22.77778 3.622731
q_gender | .6111111 .5016313
economist | .1666667 .3834825
perc_multi~2 | 51.94444 20.39744
perc_multi~1 | 3.5 1.043185
-------------+----------------------
Ample |
ability_l~td | .1600329 .8664755
ability_ta~d | .0808109 1.015158
q_age | 23.12766 4.29612
q_gender | .5851064 .4953455
economist | .1808511 .3869585
perc_multi~2 | 58.59574 18.3949
perc_multi~1 | 2.776596 .7641744
(est1 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Directed Attention}
Summary statistics: mean sd
for variables: ability_load_std ability_task_std q_age q_gender economist perc_multitasking_2 perc_multitasking_1
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
ability_l~td | .0077178 1.034096
ability_ta~d | -.1013208 .9314255
q_age | 24.3931 5.080322
q_gender | .5448276 .4997126
economist | .1586207 .3665883
perc_multi~2 | 51.30345 20.69095
perc_multi~1 | 3.234483 .8417392
-------------+----------------------
20 |
ability_l~td | -.0953546 .8044514
ability_ta~d | .0859819 .958236
q_age | 23.14286 3.764866
q_gender | .5952381 .4967958
economist | .1428571 .3541688
perc_multi~2 | 52.64286 18.76403
perc_multi~1 | 3.142857 .7513055
-------------+----------------------
40 |
ability_l~td | .2767103 .9146411
ability_ta~d | .2062629 .7104906
q_age | 25.63158 10.92505
q_gender | .3684211 .4955946
economist | .1052632 .3153018
perc_multi~2 | 62.78947 20.63863
perc_multi~1 | 2.789474 .976328
-------------+----------------------
Ample |
ability_l~td | -.1081175 .9676196
ability_ta~d | .1208537 .9243445
q_age | 23.32979 3.535954
q_gender | .6170213 .4887197
economist | .1276596 .3354997
perc_multi~2 | 61.6383 18.29381
perc_multi~1 | 2.659574 .8237495
(est2 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Forced Choice}
Summary statistics: mean sd
for variables: ability_load_std ability_task_std q_age q_gender economist perc_multitasking_2 perc_multitasking_1
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
ability_l~td | -.007574 .9835673
ability_ta~d | -.0145027 1.011907
q_age | 23.69565 4.370787
q_gender | .5144928 .5016107
economist | .173913 .3804155
perc_multi~2 | 53.42754 19.04466
perc_multi~1 | 3.181159 .7372815
-------------+----------------------
20 |
ability_l~td | .2824302 .8280313
ability_ta~d | .2309059 .7403143
q_age | 23.625 4.661284
q_gender | .65 .4830459
economist | .1 .3038218
perc_multi~2 | 56.425 21.2046
perc_multi~1 | 3.075 .7970297
-------------+----------------------
40 |
ability_l~td | -.1740166 1.230358
ability_ta~d | -.471418 1.273798
q_age | 22.8 3.13889
q_gender | .65 .4893605
economist | .1 .3077935
perc_multi~2 | 59.35 13.65081
perc_multi~1 | 3.35 .6708204
-------------+----------------------
Ample |
ability_l~td | -.0853061 1.137883
ability_ta~d | -.1319161 1.045988
q_age | 24.73958 6.090968
q_gender | .5520833 .4998903
economist | .15625 .3649982
perc_multi~2 | 57.51042 18.36873
perc_multi~1 | 2.635417 .6508261
(est3 stored)
.
. * copy mean matrix such that p-values vector has the correct length etc.
. matrix p_values=e(mean)
. local i=0
. foreach var of varlist ability_load_std ability_task_std q_age q_gender economist perc_multitasking_2 perc_multitasking_1 {
2. local i=1+`i'
3. kwallis `var' , by(treatment_id)
4. local p=chi2tail(`r(df)',`r(chi2_adj)')
5. matrix p_values[1,`i']=`p'
6. }
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 61428.00 |
| 2 | 43 | 19871.00 |
| 3 | 18 | 8593.50 |
| 4 | 94 | 44705.50 |
| 5 | 145 | 65500.50 |
|----------+-----+----------|
| 6 | 42 | 17802.50 |
| 7 | 19 | 9984.00 |
| 8 | 94 | 38621.50 |
| 9 | 138 | 60830.50 |
| 10 | 40 | 20974.50 |
|----------+-----+----------|
| 11 | 20 | 8295.00 |
| 12 | 96 | 41671.50 |
+---------------------------+
chi-squared = 10.448 with 11 d.f.
probability = 0.4906
chi-squared with ties = 10.569 with 11 d.f.
probability = 0.4801
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 64730.00 |
| 2 | 43 | 20658.00 |
| 3 | 18 | 8965.00 |
| 4 | 94 | 43585.00 |
| 5 | 145 | 59360.00 |
|----------+-----+----------|
| 6 | 42 | 19860.50 |
| 7 | 19 | 9316.50 |
| 8 | 94 | 44307.50 |
| 9 | 138 | 61030.00 |
| 10 | 40 | 19581.00 |
|----------+-----+----------|
| 11 | 20 | 7125.50 |
| 12 | 96 | 39759.00 |
+---------------------------+
chi-squared = 11.959 with 11 d.f.
probability = 0.3667
chi-squared with ties = 12.163 with 11 d.f.
probability = 0.3515
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 60712.00 |
| 2 | 43 | 19325.50 |
| 3 | 18 | 6986.50 |
| 4 | 94 | 38487.50 |
| 5 | 145 | 69592.00 |
|----------+-----+----------|
| 6 | 42 | 17176.50 |
| 7 | 19 | 8922.50 |
| 8 | 94 | 41730.00 |
| 9 | 138 | 61793.00 |
| 10 | 40 | 17457.50 |
|----------+-----+----------|
| 11 | 20 | 8221.50 |
| 12 | 96 | 47873.50 |
+---------------------------+
chi-squared = 11.789 with 11 d.f.
probability = 0.3797
chi-squared with ties = 11.905 with 11 d.f.
probability = 0.3708
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 64903.00 |
| 2 | 43 | 18197.00 |
| 3 | 18 | 8416.00 |
| 4 | 94 | 42860.00 |
| 5 | 145 | 63509.00 |
|----------+-----+----------|
| 6 | 42 | 19340.00 |
| 7 | 19 | 6827.00 |
| 8 | 94 | 44198.00 |
| 9 | 138 | 58576.00 |
| 10 | 40 | 19396.00 |
|----------+-----+----------|
| 11 | 20 | 9698.00 |
| 12 | 96 | 42358.00 |
+---------------------------+
chi-squared = 6.351 with 11 d.f.
probability = 0.8490
chi-squared with ties = 8.608 with 11 d.f.
probability = 0.6580
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 62511.00 |
| 2 | 43 | 18613.00 |
| 3 | 18 | 8196.00 |
| 4 | 94 | 43396.00 |
| 5 | 145 | 65503.00 |
|----------+-----+----------|
| 6 | 42 | 18678.00 |
| 7 | 19 | 8131.00 |
| 8 | 94 | 41166.00 |
| 9 | 138 | 63282.00 |
| 10 | 40 | 17024.00 |
|----------+-----+----------|
| 11 | 20 | 8512.00 |
| 12 | 96 | 43266.00 |
+---------------------------+
chi-squared = 1.643 with 11 d.f.
probability = 0.9994
chi-squared with ties = 4.371 with 11 d.f.
probability = 0.9578
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 62255.00 |
| 2 | 43 | 16477.50 |
| 3 | 18 | 7250.00 |
| 4 | 94 | 45948.00 |
| 5 | 145 | 57597.00 |
|----------+-----+----------|
| 6 | 42 | 17288.00 |
| 7 | 19 | 10329.50 |
| 8 | 94 | 49523.00 |
| 9 | 138 | 57357.50 |
| 10 | 40 | 18723.00 |
|----------+-----+----------|
| 11 | 20 | 10136.50 |
| 12 | 96 | 45393.00 |
+---------------------------+
chi-squared = 28.195 with 11 d.f.
probability = 0.0030
chi-squared with ties = 28.334 with 11 d.f.
probability = 0.0029
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 66141.50 |
| 2 | 43 | 22476.00 |
| 3 | 18 | 10447.50 |
| 4 | 94 | 35759.00 |
| 5 | 145 | 73276.50 |
|----------+-----+----------|
| 6 | 42 | 20319.50 |
| 7 | 19 | 7345.00 |
| 8 | 94 | 32053.00 |
| 9 | 138 | 68915.50 |
| 10 | 40 | 18476.50 |
|----------+-----+----------|
| 11 | 20 | 11093.00 |
| 12 | 96 | 31975.00 |
+---------------------------+
chi-squared = 68.690 with 11 d.f.
probability = 0.0001
chi-squared with ties = 79.449 with 11 d.f.
probability = 0.0001
.
. matrix p_values=p_values[1,1..7]
. matrix coleq p_values=p-value p-value p-value p-value p-value p-value
.
. * Convert p-values to estimation result and store it
. convert p_values
p_values[1,7]
p-value: p-value: p-value: p-value: p-value: p-value: p-value:
ability_l~td ability_ta~d q_age q_gender economist perc_multi~2 perc_multi~1
mean .48007895 .35150558 .37080276 .6580305 .95777448 .00287702 1.886e-12
. eststo p_values
.
. esttab est* p_values using `"${PATH_OUT}/tableO_1.tex"', ///
> main(mean %5.2f) aux(sd %5.2f) nostar unstack ///
> noobs nonote label append booktabs compress ///
> nonumber nomtitles frag ///
> mgroups("\textsc{Baseline}" "\textsc{Directed Attention}" "\textsc{Forced Choice}" "Kruskal-Wallis" , ///
> pattern(1 1 1 1) prefix(\multicolumn{@span}{c}{) suffix(}) span erepeat(\cmidrule(lr){@span})) ///
>
(output written to /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/tableO_1.tex)
.
.
. * As tabstat uses only observation with no missings, perform second part where only data from certain waves are available
. estimates clear
. bysort Treatment_Environment: eststo: estpost tabstat raven_score treatment_id, by(Treatment_Incentives) nototal statistics(mean sd) columns(statistics) listwise
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Baseline}
Summary statistics: mean sd
for variables: raven_score treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
raven_score | 6.125 1.481464
treatment_id | 1 0
-------------+----------------------
20 |
raven_score | 5.976744 1.388531
treatment_id | 2 0
-------------+----------------------
40 |
raven_score | 6.722222 1.48742
treatment_id | 3 0
-------------+----------------------
Ample |
raven_score | 6.086957 1.871732
treatment_id | 4 0
(est1 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Directed Attention}
Summary statistics: mean sd
for variables: raven_score treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
raven_score | 6.173469 1.579674
treatment_id | 5 0
-------------+----------------------
20 |
raven_score | 6.214286 1.881044
treatment_id | 6 0
-------------+----------------------
40 |
raven_score | 6.842105 1.641922
treatment_id | 7 0
-------------+----------------------
Ample |
raven_score | 6.195652 1.627808
treatment_id | 8 0
(est2 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Forced Choice}
Summary statistics: mean sd
for variables: raven_score treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
raven_score | 5.934066 1.533349
treatment_id | 9 0
-------------+----------------------
20 |
raven_score | 6.475 1.518898
treatment_id | 10 0
-------------+----------------------
40 |
raven_score | 6.3 1.838191
treatment_id | 11 0
-------------+----------------------
Ample |
raven_score | 6.0625 1.972214
treatment_id | 12 0
(est3 stored)
.
. * copy mean matrix such that p-values vector has the correct length etc.
. matrix p_values=e(mean)
. local i=0
. foreach var of varlist raven_score treatment_id{
2. local i=1+`i'
3. kwallis `var' , by(treatment_id)
4. local p=chi2tail(`r(df)',`r(chi2_adj)')
5. matrix p_values[1,`i']=`p'
6. }
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 96 | 28235.00 |
| 2 | 43 | 12149.50 |
| 3 | 18 | 6393.50 |
| 4 | 46 | 13863.00 |
| 5 | 98 | 29883.00 |
|----------+-----+----------|
| 6 | 42 | 13495.50 |
| 7 | 19 | 7402.00 |
| 8 | 46 | 14270.50 |
| 9 | 91 | 24656.50 |
| 10 | 40 | 13312.00 |
|----------+-----+----------|
| 11 | 20 | 6197.00 |
| 12 | 48 | 14670.50 |
+---------------------------+
chi-squared = 11.825 with 11 d.f.
probability = 0.3769
chi-squared with ties = 12.277 with 11 d.f.
probability = 0.3432
Kruskal-Wallis equality-of-populations rank test
+---------------------------+
| treatm~d | Obs | Rank Sum |
|----------+-----+----------|
| 1 | 143 | 10296.00 |
| 2 | 43 | 7095.00 |
| 3 | 18 | 3519.00 |
| 4 | 94 | 23641.00 |
| 5 | 145 | 53795.00 |
|----------+-----+----------|
| 6 | 42 | 19509.00 |
| 7 | 19 | 9405.00 |
| 8 | 94 | 51841.00 |
| 9 | 138 | 92115.00 |
| 10 | 40 | 30260.00 |
|----------+-----+----------|
| 11 | 20 | 15730.00 |
| 12 | 96 | 81072.00 |
+---------------------------+
chi-squared = 876.708 with 11 d.f.
probability = 0.0001
chi-squared with ties = 891.000 with 11 d.f.
probability = 0.0001
.
. matrix p_values=p_values[1,1..2]
. matrix coleq p_values=p-value p-value
.
. * Convert p-values to estimation result and store it
. convert p_values
p_values[1,2]
p-value: p-value:
raven_score treatment_id
mean .34319171 5.34e-184
. eststo p_values
.
. esttab est* p_values using `"${PATH_OUT}/tableO_1.tex"', ///
> append frag ///
> drop(treatment_id) /// refcat(raven_score "\emph{2nd Wave only}", nolabel) nobaselevels ///
> main(mean %5.2f) aux(sd %5.2f) nostar unstack ///
> eqlabels(none) nolines ///
> noobs nonote label booktabs compress ///
> nomtitles nodepvar nonumber
(output written to /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/tableO_1.tex)
.
. estimates clear
. bysort Treatment_Environment: eststo: estpost tabstat original_lab treatment_id, by(Treatment_Incentives) nototal statistics(mean sd) columns(statistics) listwise
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Baseline}
Summary statistics: mean sd
for variables: original_lab treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
original_lab | .6573427 .4762662
treatment_id | 1 0
-------------+----------------------
20 |
original_lab | 0 0
treatment_id | 2 0
-------------+----------------------
40 |
original_lab | 0 0
treatment_id | 3 0
-------------+----------------------
Ample |
original_lab | 1 0
treatment_id | 4 0
(est1 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Directed Attention}
Summary statistics: mean sd
for variables: original_lab treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
original_lab | .662069 .4746445
treatment_id | 5 0
-------------+----------------------
20 |
original_lab | 0 0
treatment_id | 6 0
-------------+----------------------
40 |
original_lab | 0 0
treatment_id | 7 0
-------------+----------------------
Ample |
original_lab | 1 0
treatment_id | 8 0
(est2 stored)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-> \textsc{Forced Choice}
Summary statistics: mean sd
for variables: original_lab treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
original_lab | .6449275 .4802786
treatment_id | 9 0
-------------+----------------------
20 |
original_lab | 0 0
treatment_id | 10 0
-------------+----------------------
40 |
original_lab | 0 0
treatment_id | 11 0
-------------+----------------------
Ample |
original_lab | 1 0
treatment_id | 12 0
(est3 stored)
. esttab est* using `"${PATH_OUT}/tableO_1.tex"', ///
> append frag drop(treatment_id) ///
> main(mean %4.0g) nostar unstack ///
> eqlabels(none) ///
> noobs nonote label booktabs compress ///
> nomtitles nodepvar nonumber
(output written to /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/tableO_1.tex)
.
. estimates clear
. bysort Treatment_Environment: eststo: estpost tabstat obs treatment_id, by(Treatment_Incentives) nototal statistics(mean sd) columns(statistics) listwise
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-> \textsc{Baseline}
Summary statistics: mean sd
for variables: obs treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
obs | 143 0
treatment_id | 1 0
-------------+----------------------
20 |
obs | 43 0
treatment_id | 2 0
-------------+----------------------
40 |
obs | 18 0
treatment_id | 3 0
-------------+----------------------
Ample |
obs | 94 0
treatment_id | 4 0
(est1 stored)
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-> \textsc{Directed Attention}
Summary statistics: mean sd
for variables: obs treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
obs | 145 0
treatment_id | 5 0
-------------+----------------------
20 |
obs | 42 0
treatment_id | 6 0
-------------+----------------------
40 |
obs | 19 0
treatment_id | 7 0
-------------+----------------------
Ample |
obs | 94 0
treatment_id | 8 0
(est2 stored)
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-> \textsc{Forced Choice}
Summary statistics: mean sd
for variables: obs treatment_id
by categories of: Treatment_Incentives
Treatment_In | e(mean) e(sd)
-------------+----------------------
10 |
obs | 138 0
treatment_id | 9 0
-------------+----------------------
20 |
obs | 40 0
treatment_id | 10 0
-------------+----------------------
40 |
obs | 20 0
treatment_id | 11 0
-------------+----------------------
Ample |
obs | 96 0
treatment_id | 12 0
(est3 stored)
. esttab est* using `"${PATH_OUT}/tableO_1.tex"', ///
> append frag drop(treatment_id) ///
> main(mean %5.0g) nostar unstack ///
> eqlabels(none) ///
> noobs nonote label booktabs compress ///
> nomtitles nodepvar nonumber
(output written to /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/tableO_1.tex)
.
. qui file open table_out using `"${PATH_OUT}/tableO_1.tex"', write append
. file write table_out "\bottomrule" _n
. file write table_out "\end{tabular}" _n
. file close table_out
.
.
.
. log close
name: <unnamed>
log: /Users/jonasradbruch/Dropbox/PhD/channels_defaults/Interventions and Cognitive Spillovers/Final_Documents/ReplicationPackage/EmpiricalAnalysis/out/Randomization_Check.lo
> g
log type: text
closed on: 4 Nov 2021, 09:55:52
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