Comparing groups in regression models for binary outcomes

Σχετικά έγγραφα
Principles of Workflow in Data Analysis

Γενικευμένα Γραμμικά Μοντέλα (GLM) Επισκόπηση

Statistics 104: Quantitative Methods for Economics Formula and Theorem Review

SECTION II: PROBABILITY MODELS

Probability and Random Processes (Part II)

Biostatistics for Health Sciences Review Sheet

PENGARUHKEPEMIMPINANINSTRUKSIONAL KEPALASEKOLAHDAN MOTIVASI BERPRESTASI GURU TERHADAP KINERJA MENGAJAR GURU SD NEGERI DI KOTA SUKABUMI

5.4 The Poisson Distribution.

Ανάκτηση Πληροφορίας

( ) ( ) STAT 5031 Statistical Methods for Quality Improvement. Homework n = 8; x = 127 psi; σ = 2 psi (a) µ 0 = 125; α = 0.

Εισαγωγή στην Ανάλυση Διακύμανσης

Principles of Workflow in Data Analysis

Group 2 Methotrexate 7.5 mg/week, increased to 15 mg/week after 4 weeks. Methotrexate 7.5 mg/week, increased to 15 mg/week after 4 weeks

Παράδειγμα: Γούργουλης Βασίλειος, Επίκουρος Καθηγητής Τ.Ε.Φ.Α.Α.-Δ.Π.Θ.

Interpretation of linear, logistic and Poisson regression models with transformed variables and its implementation in the R package tlm

Does anemia contribute to end-organ dysfunction in ICU patients Statistical Analysis

Επιστηµονική Επιµέλεια ρ. Γεώργιος Μενεξές. Εργαστήριο Γεωργίας. Viola adorata

Λογαριθμικά Γραμμικά Μοντέλα Poisson Παλινδρόμηση Παράδειγμα στο SPSS

Kansas Culture Change Instrument KCCI. resident centered care, a homelike environment, staff/resident relationships, staff

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

519.22(07.07) 78 : ( ) /.. ; c (07.07) , , 2008

τατιςτική ςτην Εκπαίδευςη II

2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits.


Παράδειγμα: Γούργουλης Βασίλειος, Επίκουρος Καθηγητής Τ.Ε.Φ.Α.Α.-Δ.Π.Θ.

CE 530 Molecular Simulation

Παιδιατρική ΒΟΡΕΙΟΥ ΕΛΛΑΔΟΣ, 23, 3. Γ Παιδιατρική Κλινική, Αριστοτέλειο Πανεπιστήμιο, Ιπποκράτειο Νοσοκομείο Θεσσαλονίκης, 2

APPENDICES APPENDIX A. STATISTICAL TABLES AND CHARTS 651 APPENDIX B. BIBLIOGRAPHY 677 APPENDIX C. ANSWERS TO SELECTED EXERCISES 679

CSAE Working Paper WPS/

Homework 8 Model Solution Section

)# * ' +," -.(. / ( 01(#(' ( 0 #('( +' ")# *'+,"+ (. 20#('( / )%34"5 "+56336"% (%1/ :8;434(

1. Hasil Pengukuran Kadar TNF-α. DATA PENGAMATAN ABSORBANSI STANDAR TNF α PADA PANJANG GELOMBANG 450 nm

Ερμηνεία αποτελεσμάτων Ανάλυση διακύμανσης κατά ένα παράγοντα

Μενύχτα, Πιπερίγκου, Σαββάτης. ΒΙΟΣΤΑΤΙΣΤΙΚΗ Εργαστήριο 6 ο

HMY 799 1: Αναγνώριση Συστημάτων

Υπέρταση και Διατροφή

HOMEWORK#1. t E(x) = 1 λ = (b) Find the median lifetime of a randomly selected light bulb. Answer:

LAMPIRAN. Fixed-effects (within) regression Number of obs = 364 Group variable (i): kode Number of groups = 26

Statistics & Research methods. Athanasios Papaioannou University of Thessaly Dept. of PE & Sport Science

Repeated measures Επαναληπτικές μετρήσεις

Αν οι προϋποθέσεις αυτές δεν ισχύουν, τότε ανατρέχουµε σε µη παραµετρικό τεστ.

FORMULAS FOR STATISTICS 1

Παράδειγμα: Γούργουλης Βασίλειος, Επίκουρος Καθηγητής Τ.Ε.Φ.Α.Α. Δ.Π.Θ.

Table 1: Military Service: Models. Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 num unemployed mili mili num unemployed

Simon et al. Supplemental Data Page 1

Λυμένες Ασκήσεις για το μάθημα:

1. A fully continuous 20-payment years, 30-year term life insurance of 2000 is issued to (35). You are given n A 1

The Probabilistic Method - Probabilistic Techniques. Lecture 7: The Janson Inequality

Second Order RLC Filters

Summary of the model specified

ST5224: Advanced Statistical Theory II

η πιθανότητα επιτυχίας. Επομένως, η συνάρτηση πιθανοφάνειας είναι ίση με: ( ) 32 = p 18 1 p

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

Research on Economics and Management

Solutions to Exercise Sheet 5

Global energy use: Decoupling or convergence?

ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ

τατιστική στην Εκπαίδευση II

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

Suitable for DC-DC Converters, Voltage Regulators, Decoupling Applications for Computer Motherboards, etc. Performance Characteristics

Έλεγχος ύπαρξης στατιστικά σημαντικών διαφορών μεταξύ δύο ανεξάρτητων δειγμάτων, που ακολουθούν την κανονική κατανομή (t-test για ανεξάρτητα δείγματα)

ECE598: Information-theoretic methods in high-dimensional statistics Spring 2016

Supplementary Appendix

!"!"!!#" $ "# % #" & #" '##' #!( #")*(+&#!', & - #% '##' #( &2(!%#(345#" 6##7

Συνδυασμοί φαρμάκων στην Ουρολογία

Διδακτορική Διατριβή


Μονοπαραγοντική Ανάλυση Διακύμανσης Ανεξάρτητων Δειγμάτων

Α Καρδιολογική Κλινική ΑΠΘ, Νοσοκομείο ΑΧΕΠΑ, Θεσσαλονίκη

Potential Dividers. 46 minutes. 46 marks. Page 1 of 11

Άσκηση 11. Δίνονται οι παρακάτω παρατηρήσεις:

ΧΡΟΝΟΣΕΙΡΕΣ & ΠΡΟΒΛΕΨΕΙΣ-ΜΕΡΟΣ 7 ΕΛΕΓΧΟΙ. (TEST: Unit Root-Cointegration )

Παράδειγμα: Γούργουλης Βασίλειος, Επίκουρος Καθηγητής Τ.Ε.Φ.Α.Α.-Δ.Π.Θ.

Surface Mount Multilayer Chip Capacitors for Commodity Solutions

Για να ελέγξουµε αν η κατανοµή µιας µεταβλητής είναι συµβατή µε την κανονική εφαρµόζουµε το test Kolmogorov-Smirnov.

VBA Microsoft Excel. J. Comput. Chem. Jpn., Vol. 5, No. 1, pp (2006)

MATHACHij = γ00 + u0j + rij

From the finite to the transfinite: Λµ-terms and streams

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is

Aquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET

Σηµαντικές µεταβλητές για την άσκηση οικονοµικής ολιτικής µίας χώρας. Καθοριστικοί αράγοντες για την οικονοµική ανά τυξη.

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

6.4 Superposition of Linear Plane Progressive Waves

Περιγραφή των εργαλείων ρουτινών του στατιστικού

Inverse trigonometric functions & General Solution of Trigonometric Equations

Congruence Classes of Invertible Matrices of Order 3 over F 2

χ 2 test ανεξαρτησίας

Δείγμα (μεγάλο) από οποιαδήποτε κατανομή

Νίκος Πανταζής Βιοστατιστικός, PhD ΕΔΙΠ Ιατρικής Σχολής ΕΚΠΑ Εργαστήριο Υγιεινής, Επιδημιολογίας & Ιατρικής Στατιστικής

IMES DISCUSSION PAPER SERIES

Προσοµοίωση Εξέτασης στο µάθηµα του Γεωργικού Πειραµατισµού

ΑΝΑΛΥΣΗ ΔΕΔΟΜΕΝΩΝ. Δρ. Βασίλης Π. Αγγελίδης Τμήμα Μηχανικών Παραγωγής & Διοίκησης Δημοκρίτειο Πανεπιστήμιο Θράκης

4.4 Superposition of Linear Plane Progressive Waves

The Simply Typed Lambda Calculus

ΑΓΓΛΙΚΑ Ι. Ενότητα 7α: Impact of the Internet on Economic Education. Ζωή Κανταρίδου Τμήμα Εφαρμοσμένης Πληροφορικής

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

Second Order Partial Differential Equations

Math221: HW# 1 solutions

Transcript:

ICPSRSuerProgra Coparinggroupsin regressionodelsfor binaryoutcoes ScottLong IndianaUniversity BlalockLecture August2010 Arethe effects ofproductivityontenurethesaeforenandoen? 1. Acoonsolutionforcoparinggroups: a. Estiateodelforoen. b. Estiatesaeodelforen. c. Coparecoefficientsacrossgroups. d. Concludeeithertheyarethesaeortheyarenot. 2. Toprobles: a. NRCpaneldidnotfindthecoefficientsinforative. b. PaulAllisonsenteaorkingpaperthatsaid: Differencesintheestiatedcoefficientstellusnothingaboutthe differencesintheunderlyingipactof[publications]on[tenurefor]the togroups.

1. RevieethodsforcoparinggroupsintheLRM. 2. Reviebinarylogitandprobit(BRM)intersof: a. Alatentvariableodelfory*. b. AprobabilityodelforPr(y=1 x). 3. WhyisthereaproblecoparingcoefficientsacrossgroupsinBRM? 4. ToapproachestocoparinggroupsinBRM: a. Briefly:Allison'stestsforcoparingcoefficients. b. Indepth:Usingpredictedprobabilitiestocoparegroups. Men: Woen: y art icles prestige prestige y articl es prestige prestige 1. Doenandoenhavethesaereturnfor? A : H 0 2. Wecoputeattest: ˆ ˆ t ˆ ˆ Var Var 3. Wecouldtestthatallcoefficientsareequal: B : ; ; H0 B 4. Critically, H0 thisdoesnotiply: C 2 2 H 0 : R R prestige prestige

1. Testing H 0: isappropriateinlrm. 2. IntheBRMthetestconfounds: a. Groupdifferencesintheeffectofx. b. Groupdifferencesinunexplainedvariation. 3. ToapproachescanbeusedfortheBRM: a. Allison'stestthatassueseffectsofothervariablesareequalacross groups. b. Testscoparingpredictedprobabilities. Pr y 1 x F0 xxzz Logit Probit y x0 xxzz exp 0 xx 1 exp x Pr 1 z y x x z Pr 1 0 0 x x z z 2 0xxzz 1 t dt 2 2 z z

1. Duyonly:Useonlyaduyvariableforgroup. 2. Interactions:Allogroupdifferencesintheeffectsofthepredictors suchas and. a. Testtheequalityofcoefficients. b. Coparepredictionsacrossgroups. y Pr y 1 Pr 1 x x Variable Mean StdDev Miniu Maxiu Label ------------------ tenure 0.12 0.33 0.00 1.00 Is tenured? feale 0.38 0.48 0.00 1.00 Scientist is feale? year 3.86 2.30 1.00 10.00 Years in rank. yearsq 20.17 22.15 1.00 100.00 Years in rank squared. select 5.00 1.41 1.00 7.00 Selectivity of bachelor's 7.05 6.58 0.00 73.00 Total nuber of. prestige 2.65 0.78 0.65 4.80 Prestige of departent. presthi 0.05 0.21 0.00 1.00 Prestige is 4 or higher? N = 2797 Pr tenure 1 x 0 fealefeale yearyear+ yearsqyearsq s electselect presthipresthi logit (N=2797): Factor Change in Odds Odds of: Tenure vs NoTenure tenure b z P> z e^b e^bstdx feale -0.35260-2.677 0.007 0.7029 0.8429 year 1.69865 10.426 0.000 5.4666 49.9816 yearsq -0.12295-8.748 0.000 0.8843 0.0656 select 0.12228 2.699 0.007 1.1301 1.1878 0.04948 5.986 0.000 1.0507 1.3845 presthi -1.05052-2.662 0.008 0.3498 0.8009 _cons -7.59000-15.025 0.000 b = ra coefficient z = z-score for test of b=0 P> z = p-value for z-test e^b = exp(b) = factor change in odds for unit increase in X e^bstdx = exp(b*sd of X) = change in odds for SD increase in X

1. Odds xz, 2. Odds: Pr y 1 x, z Pr y 0 x, z Oddsratios: Oddsx1, z exp x Odds xz, exp 0.70. 3. Oddsratioforfeale: feale Beingafealescientistdecreasestheoddsoftenurebyafactorof.70, holdingallothervariablesconstant. exp 1.05. Foreachadditionalarticle,theoddsoftenureincreasebyafactorof1.05, holdingallothervariablesconstant. 2. Oddsratiofor: Botharroscorrespondtothesaeoddsratio. 1. Coputethepredictedprobabilityatspecificvaluesoftheindependent variables: 0 feale feale yearyear+ yearsqyearsq Pr tenure 1 x selectselect presthipresthi 2. Forexaple,theprobabilityoftenurefornonpublishingoeninyear7, ithselectivity4andloprestige: 0 feale 1 year 7yearsq 49 0.16 select 4 0 presthi.05 3. Extendingthisidea,plotsofprobabilitiescanbeconstructed...

Pr y 1 x F0 x z x z For average scientists in year seven Probability of Tenure 0.2.4.6.8 1 Woen Men Nuber of Articles #3 groups02_argins.do jsl 2010-07-28 1. Probabilityoftenureisabout.06higherforenatalllevelsofproductivity. 2. Lackofinteractionsithgenderisunrealistic. 1. IntheBRM: W oen: Pry 1 ar ticles prest ige prestige Men: Pry 1 presti ge prestige 2. CaneuseaChotypetest? : H0 3. Allison(1999)shothatbecauseofanidentificationproble,theusual testsofthishypothesistellsusnothingabouttheunderlyingipactof forenandoen.

1. Structuralodelithalatenty*: y x 2. 3. 4. Errorisnoral(0,1)forprobit;islogistic(0, 2 /3)forlogit. Observedyandlatenty*arelinkedby: 1 if y 0 y 0 if y 0 Graphically 5. Theprobabilitydependsontheerrordistributionandthecoefficients: y x y x Pr 1 Pr 0 Pr x x 6. Thereisanidentificationproblethatcanbeillustratedgraphically.

GroupW:=12,=2,=2 GroupM:=6,=1,=1 7. The effect (i.e.,)ofxisticeaslargeforwthanm. 8. Intersof Pr( y 1),theseMandWareepiricallyindistinguishable: ForW: Achangeof1inxhen=2and=2. ForM: Achangeof1inxhen=1and=1. 1. Lety*bethelatentvariableassociatedithreceiptoftenure: Woen: y Men: y 2. Assuethecoefficientsforareequal: 3. Assueoenhaveoreunexplainedvariation(hyouldthey?): 2 2 4. Whenyouestiatetheodel,thesoftareakesiplicitassuptions: Logit:Var 2 /3 Probit:Var 1 5. Whatistheeffectoftheseiplicitassuptions? 6. Withprobit,isrescaledsothat: Var Var 1 7. Foroen,theestiatedodelforprobitis: y, here 1 8. Foren,theestiatedodelforprobitis: y, here 1

9. Weanttotest: H : NTilda o 0 s article 10. But,standardsoftareonlyallosustotest: H Tilda : 0 11. Unless, 2 2 NoTilda Tilda H is not equivalent to H 0 0 Aside: rescaling errors in logit is essier 1. Theodelis: y 2. Werescaletheerrorssothat: Var 2 3 rather than 1 for probit 3. Thisleadstotheequationthatisestiated: y 3 3 3 3 Todistinctapproachesaddresstheidentificationproble. 1. Allison'stestof H 0: x x disentanglesthe 'sandvar. a. Thetestrequiresthestrongassuption: z z z or equivalently 1 z b. Theratioof z sestatesgroupdifferencesinunexplainedvariation: z z / z 1 z z / z c. Thisprovidesleveragetotest: : H 0 x x

2. Alternatively,sinceprobabilitiesareinvarianttoVar,Iproposetesting: x x H0: Pr y 1 Pr y 1 Woen:=12,=2,=2 Men:=6,=1,=1 1. Let 1 foroen,else0and x x; let 1 foren,else0and x x. Pr y 1 x F x x x x 2.Then: x x x F x x Pr y 1 F x if 1, 0 Pr y 1 if 0, 1 3.Thegenderdifferenceintheprobabilityoftenureis: Pr y 1 Pr y 1 x x x Startithasipleodelithonlypublicationspredictingtenure: logit (N=2797): Factor Change in Odds Odds of: Tenure vs NoTenure WOMEN b z P> z e^b e^bstdx constant -2.50116-17.858 0.000 0.0820 0.2974 0.04714 4.490 0.000 1.0483 1.3150 MEN b z P> z e^b e^bstdx constant -2.72101-22.402 0.000 0.0658 0.2673 0.10239 9.756 0.000 1.1078 1.8054 ----------- b = ra coefficient z = z-score for test of b=0 P> z = p-value for z-test e^b = exp(b) = factor change in odds for unit increase in X e^bstdx = exp(b*sd of X) = change in odds for SD increase in X

#7 groups02_argins.do jsl 2010-07-28 #7 groups02_argins.do jsl 2010-07-28 #7 groups02_argins.do jsl 2010-07-28 #7 groups02_argins.do jsl 2010-07-28 Tocoparegroupsatdifferentlevelsof: 1. Coputediscretechange(aka:firstdifference): Pr y 1 Pr y 1 2. Confidenceintervalsforpredictions:, LoerBound UpperBound Withrepeatedsapling,eouldexpectthepredictedprobabilitytofall ithinthecininetyfivepercentofthetie. 3. ForCI,deltaorendpointethodareeasyandfast; bootstraprequiresatleast1,000replicationstogetreliableresults. 4. WithoneRHSvariable,ecanplotallcoparisons. 5.Movingfropredictionsforeachgrouptodifferencesinpredictions: A:Probablitiesbygroup B:DiscretechangeithCI Probability of Tenure 0.2.4.6.8 1 Woen Men Pr(en) - Pr(oen) -.1 0.1.2.3.4.5.6.7.8 Difference is not significant 95% confidence interval Nuber of Articles Nuber of Articles 6.Orusingdashedlinestoindicatedifferencesthatarenotsignificant. C:Discretechangeithbrokenline B:DiscretechangeithCI Pr(en) - Pr(oen) -.1 0.1.2.3.4.5.6.7.8 Difference is not significant Difference is significant Pr(en) - Pr(oen) -.1 0.1.2.3.4.5.6.7.8 Difference is not significant 95% confidence interval Nuber of Articles Nuber of Articles

1. 2. Addingvariablesintroducessubstantialcoplicationsforinterpretation: Withtoindependentvariables: Pr y 1 xz, F xxzz 3. Setting z Z changestheinterceptinanequationithonly x: Pr y 1 x, Z F xxzz 4. F zz xx F x x Thus,probabilitiesanddiscretechangesdependonthelevelsofeach variable. Controlvariableschangetheintercept 1. Foragiven z Z: 2. Men: Woen: Pr 1 y x Z F x x y x, Z F x x Pr 1, Differencesinprobabilitiesforagiven x dependsonthelevelofother variables: x, Z Pr y 1 x, Z Pr y 1 x, Z logit (N=2797): Factor Change in Odds Odds of: Tenure vs NoTenure WOMEN b z P> z e^b e^bstdx constant -2.60432-17.320 0.000 0.0740 0.2829 0.06761 5.358 0.000 1.0699 1.4811 presthi -1.98396-2.685 0.007 0.1375 0.7484 MEN b z P> z e^b e^bstdx constant -2.71499-22.268 0.000 0.0662 0.2681 0.10554 9.890 0.000 1.1113 1.8385 presthi -0.94529-2.058 0.040 0.3886 0.8627

Probability of Tenure 0.2.4.6.8 1 Woen - not distinguished Woen - distinguished Men - not distinguished Men - distinguished Nuber of Articles #12 groups02_argins.do jsl 2010-07-28 Pr(en) - Pr(oen) -.1 0.1.2.3.4.5.6.7.8 Distinguished if not significant Not distinguished if not significant Nuber of Articles #13 groups02_argins.do jsl 2010-07-28 logit (N= 2797): Factor Change in Odds Odds of: Tenure vs NoTenure WOMEN b z P> z e^b e^bstdx constant -5.84198-6.747 0.000 0.0029 0.0589 year 1.40777 5.472 0.000 4.0868 30.1273 yearsq -0.09559-4.364 0.000 0.9088 0.1857 select 0.05513 0.769 0.442 1.0567 1.1534 0.03395 2.693 0.007 1.0345 1.2181 prestige -0.37079-2.376 0.017 0.6902 0.6013 b = ra coefficient z = z-score for test of b=0 P> z = p-value for z-test e^b = exp(b) = factor change in odds for unit increase in X e^bstdx = exp(b*sd of X) = change in odds for SD increase in X

#18 icpsr_groups.do jsl 2009-07-15 #18 icpsr_groups_2010.do jsl 2010-07-26 #18 icpsr_groups_2010.do jsl 2010-07-26 #18 icpsr_groups_2010.do jsl 2010-07-26 logit (N= 2797): Factor Change in Odds Odds of: Tenure vs NoTenure MEN b z P> z e^b e^bstdx constant -7.68016-11.271 0.000 0.0005 0.0241 year 1.90885 8.915 0.000 6.7454 130.9789 yearsq -0.14322-7.699 0.000 0.8666 0.0622 select 0.21577 3.513 0.000 1.2408 1.7711 0.07369 6.367 0.000 1.0765 1.5299 prestige -0.43119-3.963 0.000 0.6497 0.5418 b = ra coefficient z = z-score for test of b=0 P> z = p-value for z-test e^b = exp(b) = factor change in odds for unit increase in X e^bstdx = exp(b*sd of X) = change in odds for SD increase in X Probabilitiesbygroup DiscretechangeithCI Plotted at prestige = 5 Plotted at prestige = 5 Pr(tenure) 0.2.4.6.8 1 Men Woen Pr(en) - Pr(oen) -.1.1.3.5.7 95% confidence interval Male-Feale difference Nuber of Nuber of DiscretechangeithCI Discretechangeithbrokenline Plotted at prestige = 5 Plotted at prestige = 5 Pr(en) - Pr(oen) -.1.1.3.5.7 95% confidence interval Male-Feale difference Pr(en) - Pr(oen) -.1.1.3.5.7 Nuber of Nuber of

Holdingallothervariablesconstant: Pr(en) - Pr(oen) 0.1.2.3.4.5 Weak (prestige=1) Adequate (prestige=2) Good (prestige=3) Strong (prestige=4) Distinguished (prestige=5) Nuber of #19 icpsr_groups.do jsl 2009-07-15 Holdingallothervariablesconstant: Pr(en) - Pr(oen) 0.1.2.3.4.5 no 10 20 30 40 50 1 2 3 4 5 Job Prestige #21 icpsr_groups.do jsl 2009-07-15

1. IntheLRMecanusestandardteststocoparecoefficientsacrossgroups. 2. IntheBRM,thesetestsareprobleaticduetoidentificationissues. 3. Wecanakestrongerassuptionstotestthecoefficients. 4. Testscoparingpredictedprobabilitiesareunaffectedbytheidentification proble. 1. 2. 3. Youustdealiththeinterpretationofnonlinearodelssinceasingletest isnotpossible.shouldyouadjustforultipletests? Doprobabilitiesshothe effect of(say)? Doyouhavesufficientobservationstosupportyourconclusions.Arethe preditions onthesupport? Allison,PaulD.1999.CoparingLogitandProbitCoefficientsAcrossGroups.Sociological MethodsandResearch28:186208. Cho,G.C.1960.Testsofequalitybeteensetsofcoefficientsintolinearregressions. Econoetrica28:591605. Long,J.S.2009(2005).CoparingGroupsusingPredictedOutcoes. Long,J.S.andFreese,J.2005.RegressionModelsforCategoricalandLiitedDependent VariablesithStata.SecondEdition.CollegeStation,TX:StataPress. Long,J.Scott,PaulD.Allison,andRobertMcGinnis.1993.RankAdvanceentinAcadeic Careers:SexDifferencesandtheEffectsofProductivity.AericanSociologicalRevie 58:703722. Willias,Richard.2009.UsingHeterogeneousChoiceModelstoCopareLogitandProbit CoefficientsacrossGroups.SociologicalMethods&Research37:531559. Xu,JunandLong,J.2005,Confidenceintervalsforpredictedoutcoesinregression odelsforcategoricaloutcoes.thestatajournal5:537559.

.indiana.edu/~jslsoc/index.ht Stata10at.stata.coithauxiliarySPostpackage(seeLongand Freese2005). Stata11usingargins.