------------------------------------------------------------------------------- help forseqlogit10 postestimation, for Stata versions 9 and 10-------------------------------------------------------------------------------

Title

seqlogit10 postestimation-- Postestimation tools for seqlogit10

Descriptionpost estimation tools specifically for seqlogit10:

seqlogitdecomp10Makes a graph showing a decomposition of the effect of a variable on the highest achieved level of the dependent variable into effects of that variable on passing each transition and the importance of that transition as described in (Buis 2010).

uhdesc10creates a table of describtive statistics of the unobserved variable at each transition. This is only available when thesd()option was used for seqlogit10.

seqlogit10_sensitivityis strictly speaking not a tool, but a helpfile showing how to run a sensitivity analysis withseqlogit10.

The following standard postestimation commands are also available:

command description ------------------------------------------------------------------------- INCLUDE help post_estat INCLUDE help post_estimates INCLUDE help post_lincom INCLUDE help post_lrtest INCLUDE help post_mfx INCLUDE help post_nlcom

predictpredictions INCLUDE help post_predictnl INCLUDE help post_suest INCLUDE help post_test INCLUDE help post_testnl -------------------------------------------------------------------------

------------------------------------------------------------------------------- help for

seqlogitdecomp10-------------------------------------------------------------------------------

Syntax for seqlogitdecomp10

seqlogitdecomp10,overat(overatlist)[at(atlist)levels(levellist)subtitle(titlelist)eqlabel(labellist)eqlegendxline(linearg)yline(linearg)title(title)name(name,replace)yscale(axis_suboptions)xscale(axis_suboptions)ysize(#)xsize(#)]

Description

seqlogitdecomp10displays a graph showing a decomposition of difference in the effect of a variable on the expected value of the dependent variable into effects of the variable on passing transitions and the importance if each transition (the weight) as described in (Buis 2010a). The variable whose effect will be decomposed is specified in theofinterest()option inseqlogit10. For example, the dependent variable is the highest achieved level of education and the variable of interest is parental status, thenseqlogitdecompwill decompose the effect of parental status on the highest achieved level of education into effects on passing each transition between levels of education and weights that represent the importance of that transition.The effect on the expected value can differ between groups in the population.

seqlogitdecomp10shows how these differences are due to differences in effects on the transitions across groups and differences in the importance of each transition across groups. To continue the example: the effect of parental status can change over cohorts, and {seqlogitdecomp} will tell the extend to which this is due to changes in the effects on the transitions between levels of education or changes in the importance of each transition.

Options+--------------------------------------+ ----+ Specifying the groups to be compared +-----------------------------

overat(overlist)Specifies the values of the explanatory variables of the groups that are to be compared. It overrides any value specified in theatoption. Each comparison is seperated by a comma. The syntax foroverlistis:

varname_1# [varname_2# [...]],varname_1# [varname_2# [...]], [...]

at(atlist)specifies the values at which the equations are evaluated. The syntax foratlistis:varname# [varname# ...]. The equations will be evaluated at the mean values of any of the variables not specified inat.Say the dependent variable is highest achieved level of education, which is influenced by child's Socio Economic Status (ses) and cohort (coh) and the interaction between ses and coh (_ses_X_coh). We want to compare the decomposition of the effect of ses over different cohorts for mean value of ses. Say that coh has only three values: 1, 2, and 3 and the mean value of ses is .5. Than the

overatand {otp at} options would read:overat( coh 1, coh 2, coh 3 ) at( ses .5 )

Notice that the values for the interaction term need not be specified in the

overat()option, as long as it was created using theover()option in seqlogit10.

+---------------+ ----+ Other options +----------------------------------------------------

levels(levellist)specifies the values attached to each level of the dependent variable. If it is not specified the values of the dependent variabel will be used. The syntax forlevelsis: # = # [, # = #, ...]

subtitel(titlelist)specifies the titles above each group, cohort in the example above. The syntax oftitlelistis "string" "string" [...]. The number of titles must equal the number of groups.

eqlabel(labellist)specifies labels for each transition. The syntax oflabellistis "string" "string" [...]. The number of labels must equal the number of transitions. If one wants to let the label span more than one line, one can use `" "string1" "string2" "'.

eqlegendspecifies that a legend is used to identify the different transitions. By default the transitions are identified using titles on the right of the graph.

xline(numlist)see: added line options

yline(numlist)see: added line options

title(title)see: title_options

name(name,replace)see: name_option

[y|x]scale(axis sub options)see: axis_scale_options

[y|x]lable(rule_or_values)see: axis_options

[y|x]size(#)see: region_options

Example

sysuse nlsw88, cleargen ed = cond(grade< 12, 1, ///cond(grade==12, 2, ///cond(grade<16,3,4))) if grade < .gen byr = (1988-age-1950)/10gen white = race == 1 if race < .

seqlogit10 ed byr south, ///ofinterest(white) over(byr) ///tree(1 : 2 3 4, 2 : 3 4, 3 : 4) ///levels(1=6, 2=12, 3=14, 4= 16) ///or

seqlogitdecomp10, ///overat(byr -.5, byr 0, byr .4) ///subtitle("1945" "1950" "1954") ///eqlabel(`""finish" "high school""' ///`""high school v" "some college""' ///`""some college v" "college""') ///xline(0) yline(0)

------------------------------------------------------------------------------- help for

uhdesc10-------------------------------------------------------------------------------

Syntax for uhdesc10

uhdesc10,[at(atlist)overat(overatlist)levels(levellist)overlab(stringlist)draws(#)]

Description

uhdesc10creates a table of describtive statistics of the unobserved variable at each transition. This is only available when thesd()option was used for seqlogit10. When thesd()option is specified one is estimating the parameters that would occur if there is an unobserved variable, which is normally distributed, wich at the first transition has a mean of zero, a standard deviation as specified in thesd()option, and is uncorrelated witht the observed covariates, and one correctly controlled for this unobserved variable. The consequences of such an unobserved variable and the way to estimate the parameters in such a scenario are discussed in (Buis 2011). The aim ofuhdesc10is to show what happens to this unobserved variable at the different transitions, and thus get an insight into why the estimates in the scenario are different (or not) from a regular sequential logit.

Options

overat(overlist)Specifies the values of the explanatory variables of the groups that are to be compared. It overrides any value specified in theatoption. Each comparison is seperated by a comma. The syntax foroverlistis:

varname_1# [varname_2# [...]],varname_1# [varname_2# [...]], [...]

at(atlist)specifies the values at which the equations are evaluated. The syntax foratlistis:varname# [varname# ...]. The equations will be evaluated at the mean values of any of the variables not specified inat.Say the dependent variable is highest achieved level of education, which is influenced by child's Socio Economic Status (ses) and cohort (coh) and the interaction between ses and coh (_ses_X_coh). We want to compare the decomposition of the effect of ses over different cohorts for mean value of ses. Say that coh has only three values: 1, 2, and 3 and the mean value of ses is .5. Than the

overatand {otp at} options would read:overat( coh 1, coh 2, coh 3 ) at( ses .5 )

Notice that the values for the interaction term need not be specified in the

overat()option, as long as it was created using theover()option in seqlogit10.

overlab(stringlist)specifies the label that is to be attached to each group specified in theoveratlist()option. Spaces are not allowed but an _ will be displayed as an space. The number of labels has to be the same as the number of groups specified in theoveratlist()option.To continue the example above: Say that a value of 1 on the variable coh corresponds to the cohort born in 1950, a value 2 corresponds to the cohort born in 1970, the value 3 corresponds to the cohort born in 1990, then the {cmd overlab()} option would read:

overlab(1950 1970 1990)

levels(levellist)specifies the values attached to each level of the dependent variable. If it is not specified the values of the dependent variabel will be used. The syntax forlevelsis: # = # [, # = #, ...]

Example

sysuse nlsw88, cleargen ed = cond(grade< 12, 1, ///cond(grade==12, 2, ///cond(grade<16,3,4))) if grade < .gen byr = (1988-age-1950)/10gen white = race == 1 if race < .

seqlogit10 ed byr south, ///ofinterest(white) over(byr) ///tree(1 : 2 3 4, 2 : 3 4, 3 : 4) ///or sd(1)uhdesc10

------------------------------------------------------------------------------- help for

predict-------------------------------------------------------------------------------

Syntax for predict

predict[type]newvar[if] [in] [,statisticoutcome(#)transition(#)choice(#)equation(#)levels(levellist)]

statisticDescription -------------------------------------------------------------------------xbxb, fitted valuesstdpstandard error of the predictiontrprprobability of passing transitiontratriskproportion of respondents at risk of passing transitiontrvarvariance of the indicator variable indicating whether or not the respondent passed the transitiontrgaindifference in expected highest achieved level between those that pass the transition and those that do nottrweightweight assigned to transitionprprobability that an outcome is the highest achieved outcome.yexpected highest achieved leveleffectEffect of variable of interest on expected highest achieved level. This variable is specified in theofinterest()option inseqlogit. Interactions with the variables specified in theover()option ofseqlogitare automatically taken into account.residualsdifference between highest achieved level and expected highest achieved level.scorefirst derivative of the log likelihood with respect to the linear predictor. -------------------------------------------------------------------------

Options for predict

transition(#)specifies the transition, 1 is the first transition specified in thetreeoption inseqlogit, 2 the second, etc.

choice(#)specifies the choice within the transition, 0 is the choice (the reference category), 1 the second, etc.

equation(#)specifies the equation, #1 is the first equation, #2 the second, etc.

levels(levellist)specifies the values attached to each level of the dependent variable. If it is not specified the values of the dependent variabel will be used. The syntax forlevelsis: # = # [, # = #, ...]

ReferencesBuis, Maarten L. 2010 ``Chapter 6, Not all transitions are equal: The relationship between inequality of educational opportunities and inequality of educational outcomes'', In: Buis, Maarten L. ``Inequality of Educational Outcome and Inequality of Educational Opportunity in the Netherlands during the 20th Century''. PhD thesis. http://www.maartenbuis.nl/dissertation/chap_6.pdf

Buis, maarten L. 2011 ``The Consequences of Unobserved Heterogeneity in a Sequential Logit Model'', Research in Social Stratification and Mobility, 29(3), pp. 247-262. http://dx.doi.org/10.1016/j.rssm.2010.12.006

Also seeOnline: help for

seqlogit,estimates,lincom,lrtest,mfx,nlcom,predictnl,suest,test,testnl