I really thank everyone here sparing no efforts to help me.
I have a censored dataset and the regression is an inverted U-relationship.
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Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte(M control1 control2 control3 control4 control5 control6) int x double(y control7 control8) 1 0 0 0 0 1 0 8 22.949106216430664 17.3120174407959 20.570825576782227 0 1 1 1 0 1 0 18 22.806461334228516 16.588098526000977 18.744325637817383 1 1 0 0 0 4 1 8 17.978151321411133 17.216707229614258 .6931471824645996 0 0 0 1 0 1 0 123 16.005598068237305 16.300416946411133 18.9520320892334 1 0 0 1 0 1 0 5 17.918004989624023 17.034385681152344 15.428786277770996 0 1 0 1 1 1 0 346 24.482324600219727 17.399028778076172 20.355924606323242 1 1 0 1 1 1 0 3 24.223512649536133 18.450239181518555 17.617250442504883 0 0 0 0 0 1 0 96 23.566471099853516 16.811243057250977 16.955846786499023 0 1 0 0 1 2 0 425 23.66777801513672 18.19753646850586 18.775419235229492 0 0 0 1 0 1 0 106 23.174531936645508 17.370859146118164 16.89447021484375 1 1 0 1 0 1 0 4 17.732799530029297 14.457364082336426 19.205141067504883 1 0 0 1 0 1 1 3 15.683768272399902 14.457364082336426 .6931471824645996 0 1 0 1 0 2 0 63 22.443294525146484 17.7275333404541 19.00855827331543 1 0 0 0 0 2 0 8 18.52099609375 16.11809539794922 13.792720794677734 0 0 1 1 0 1 0 9 13.517104148864746 19.04928970336914 18.136098861694336 1 0 0 0 0 1 0 6 15.053014755249023 14.457364082336426 19.068098068237305 0 0 1 0 0 1 0 697 23.785768508911133 17.504390716552734 19.758201599121094 0 1 0 1 1 2 0 46 23.127647399902344 17.822843551635742 18.129066467285156 1 0 0 0 0 2 0 113 17.74494171142578 14.508657455444336 14.646207809448242 0 0 0 1 0 3 1 125 18.34654998779297 14.375125885009766 19.459447860717773 0 1 1 1 1 1 0 107 26.6013240814209 19.806974411010742 21.029006958007813 0 1 1 1 1 1 0 107 26.275054931640625 19.5192928314209 19.718734741210938 1 0 0 0 0 1 0 11 21.269575119018555 13.815510749816895 18.251508712768555 0 1 0 0 1 1 0 4 22.68794822692871 17.281246185302734 16.724597930908203 0 0 0 1 0 1 0 105 14.990157127380371 13.815510749816895 15.718832015991211 0 0 0 1 0 1 0 663 19.204071044921875 17.034385681152344 13.799907684326172 1 0 0 1 0 1 0 4 16.33489990234375 14.508657455444336 17.44756507873535 0 0 0 0 0 1 0 8 18.20665740966797 16.380460739135742 18.75150489807129 1 0 0 1 0 1 0 3 13.334243774414063 14.457364082336426 19.18917465209961 0 0 0 1 0 1 0 284 23.10700035095215 16.523561477661133 19.209861755371094 0 1 0 1 1 2 0 284 22.16788673400879 15.424948692321777 14.695516586303711 1 1 1 1 0 1 0 8 24.212265014648438 19.035865783691406 19.782316207885742 0 0 0 1 0 1 0 455 17.6008358001709 16.811243057250977 9.2648286819458 1 1 0 0 1 1 0 2 23.746435165405273 16.86003303527832 18.270660400390625 1 0 0 1 0 2 0 5 19.581193923950195 17.281246185302734 18.4521541595459 0 0 0 1 0 1 0 5 19.14850425720215 16.21340560913086 15.823354721069336 0 0 1 0 0 1 0 106 22.485082626342773 16.11809539794922 17.567533493041992 1 1 0 0 0 1 0 7 22.783226013183594 15.761420249938965 18.496137619018555 0 0 0 1 0 1 0 11 16.819210052490234 13.527828216552734 16.94902992248535 0 0 0 1 0 1 0 151 18.90007781982422 16.11809539794922 18.147491455078125 1 0 0 0 0 1 0 8 21.86478614807129 17.034385681152344 18.850242614746094 1 1 1 1 1 1 0 7 22.845659255981445 17.68671226501465 19.689342498779297 1 1 0 1 1 1 0 6 23.92540740966797 18.132999420166016 20.34378433227539 0 0 0 1 0 1 0 13 23.123905181884766 17.909854888916016 18.01799774169922 0 0 0 1 0 3 0 3 18.898025512695313 15.761420249938965 18.995527267456055 0 0 0 1 0 1 0 5 19.191537857055664 16.01273536682129 19.141666412353516 0 1 1 0 1 1 0 42 24.29490089416504 17.7275333404541 19.795740127563477 1 0 0 1 0 1 0 8 18.446407318115234 16.883563995361328 20.610980987548828 0 0 0 0 0 1 0 5 17.829132080078125 16.01273536682129 19.647912979125977 1 1 1 1 1 1 0 6 23.370441436767578 17.622173309326172 19.004106521606445 0 1 0 1 1 1 0 175 23.807193756103516 18.980297088623047 20.575855255126953 0 0 0 0 0 1 0 284 21.572847366333008 15.424948692321777 19.118602752685547 0 0 0 1 0 1 0 109 18.238428115844727 15.068273544311523 18.99883270263672 0 1 0 0 1 1 0 5 22.323518753051758 18.035018920898438 18.701475143432617 1 1 1 1 1 1 0 4 24.551706314086914 18.951309204101563 18.1805477142334 0 0 0 1 0 5 0 46 17.35716438293457 13.815510749816895 17.30387306213379 0 0 0 0 0 1 1 279 20.36696434020996 15.894951820373535 .6931471824645996 0 1 1 1 1 2 0 18 24.85302734375 19.113828659057617 19.06422233581543 1 1 0 1 1 1 0 6 23.23371124267578 15.761420249938965 18.10226821899414 1 1 1 1 1 1 0 8 24.375486373901367 17.822843551635742 19.248655319213867 1 1 0 1 1 1 0 8 23.496232986450195 17.909854888916016 18.418119430541992 0 0 0 0 0 1 0 58 18.395998001098633 15.068273544311523 17.63210678100586 0 1 0 1 1 1 0 5 24.17245864868164 18.396387100219727 18.096141815185547 0 0 0 0 0 1 0 40 15.38599967956543 14.508657455444336 9.139273643493652 0 1 0 0 0 1 0 21 23.556793212890625 17.426427841186523 19.268308639526367 0 1 1 0 1 1 0 6 24.420333862304688 16.811243057250977 19.697742462158203 1 0 0 1 0 2 0 4 18.793746948242188 14.457364082336426 13.836281776428223 1 1 0 0 1 1 0 2 23.786779403686523 16.811243057250977 17.747819900512695 1 1 0 1 0 1 0 8 19.58517074584961 16.951004028320313 18.983076095581055 1 0 0 0 0 1 0 5 21.72478675842285 16.811243057250977 18.40504264831543 1 1 1 0 1 1 0 6 25.056909561157227 16.11809539794922 19.21035385131836 0 1 1 0 1 1 0 284 23.98286247253418 15.424948692321777 19.062726974487305 0 1 1 0 1 2 0 284 22.97431182861328 16.01273536682129 18.093008041381836 1 0 0 0 0 1 0 8 18.126632690429688 14.508657455444336 19.24971580505371 0 0 1 1 0 1 0 697 23.21192741394043 17.7275333404541 16.86979103088379 1 0 0 0 0 1 0 135 23.33150863647461 16.11809539794922 19.8182315826416 0 0 0 0 0 5 0 490 18.4140682220459 15.894951820373535 13.995794296264648 0 . . . . . . . . . . 0 0 0 1 0 1 0 697 22.618450164794922 17.504390716552734 .6931471824645996 0 0 0 1 0 1 0 161 24.22525405883789 16.845643997192383 19.180622100830078 0 0 0 0 0 1 0 63 23.49774169921875 17.281246185302734 17.358951568603516 0 0 0 1 0 1 0 663 19.229278564453125 16.300416946411133 16.765993118286133 0 0 0 0 0 1 0 58 15.912301063537598 14.747674942016602 .6931471824645996 0 1 1 0 1 1 0 284 24.110410690307617 16.11809539794922 12.027538299560547 0 0 0 0 0 1 0 40 21.205873489379883 17.370859146118164 16.865760803222656 1 0 0 1 0 1 0 56 17.881935119628906 13.815510749816895 17.762706756591797 1 0 1 1 0 1 0 4 18.35368537902832 16.11809539794922 19.24974250793457 0 0 1 0 0 1 0 777 23.53510284423828 16.11809539794922 17.638704299926758 0 1 1 1 1 1 0 109 25.289718627929688 17.822843551635742 14.394180297851563 1 0 0 1 0 2 0 8 17.924514770507813 17.676240921020508 19.183582305908203 1 1 1 0 1 1 0 11 24.805057525634766 18.643823623657227 19.623146057128906 1 1 1 0 1 1 0 11 24.311477661132813 18.31532096862793 18.698169708251953 1 1 1 1 1 1 0 12 25.720643997192383 18.951309204101563 20.346450805664063 0 1 0 1 1 1 0 6 18.496326446533203 17.034385681152344 17.243867874145508 1 1 1 1 1 1 0 6 25.264881134033203 19.5192928314209 19.64662742614746 0 0 0 1 0 1 0 40 17.51824378967285 14.457364082336426 18.340465545654297 0 1 0 0 0 1 0 151 23.607288360595703 17.216707229614258 18.674285888671875 0 1 0 0 1 1 0 9 23.45798683166504 16.811243057250977 17.900461196899414 1 0 0 1 1 1 0 5 20.373798370361328 17.553180694580078 18.21268653869629 1 0 0 0 0 1 0 2 22.999513626098633 17.504390716552734 16.867582321166992 end
M is the moderator and my model is like: tobit y x x2 M Mx Mx2 control1 control2 control3 control4 control5 control6 control7 control8
I want to study the effect of M on the turning point of the quadratic model(shifts to left or right). According to some literature, to test the moderating effect of M on X2, full specification means to include both term M × X and term M × X2 in the regression model. When testing the turning point shift, one should first use the full specification, but if the coefficient of M × X2 is not statistically different from zero, it is appropriate to drop the term M × X2. I dropped the three-way interaction and the X*M is significant. However, I don't know how to graph the original inverted U-relationship and the moderating effect of the turning point(M being 0 or 1) in STATA. I've read and tried some suggestions provided in similar posts about graphing the interaction term in the quadratic model; however, none of them seemed to work in my case.
It would be great if somebody can help me. Thank you very much in advance!
Julie
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