Computed theoretical power for N=100 and N=200 scenarios
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Modules/ado/plus/p/prgen.hlp
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Modules/ado/plus/p/prgen.hlp
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{smcl}
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{* 06Feb2010}{...}
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{hline}
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help for {hi:prgen}{right:06Feb2010}
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{hline}
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{title:Generate predicted values and confidence intervals for regression models}
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{p 4 4 2}
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To compute the predicted values with all variables but varname
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held at values specified by x() and rest(). The program extends
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{cmd:prgen} by allowing you to generate variables containing upper
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and lower bounds for confidence intervals and marginal effects.
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{p 8 15 2}{cmd:prgen} varname,
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{cmdab:g:enerate(}{it:newvar}{cmd:)}
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[{cmdab:f:rom(}{it:#}{cmd:)}
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{cmdab:t:o(}{it:#}{cmd:)}]
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[{cmd:x(}{it:variables_and_values}{cmd:)}
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{cmdab:r:est(}{it:stat}{cmd:)}
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{cmd:all}]
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[{cmdab:b:rief}
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{cmdab:max:cnt(}{it:#}{cmd:)}
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{cmdab:noba:se}
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{cmdab:nola:bel}
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{cmdab:n:cases(}{it:#}{cmd:)}
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{cmd:gap(}{it:#}{cmd:)}
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{cmdab:noi:sily}
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{cmdab:mar:ginal}
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{cmdab:con:ditional}]
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[{cmd:ci}
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{it:prvalue_options}]
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{p 4 4 2}
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where {it:variables_and_values} is an alternating list of variables
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and either numeric values or mean, median, min, max, upper, lower,
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previous.
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{p 4 4 2}
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{it:stat} is either mean, median, min, max, upper, lower, previous,
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grmean (group mean), grmedian, grmin, grmax.
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{p 4 4 2}
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See {help prvalue} for options that can be specified for computing
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confidence intervals.
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{title: Description}
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{p 4 4 2}
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{cmd:prgen} computes predicted values and confidence intervals
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for regression with continuous, categorical, and count outcomes
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in a way that is useful for making plots. Predicted values are computed
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for the case in which one independent variable varies over a specified
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range while the others are held constant. You can request variables
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containing upper and lower bounds for these variables. You can also
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create a variable containing the marginal change in the outcome with
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respect to the specified variable, holding other variabels constant. New
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variables are added to the existing dataset that contain these
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predicted values that can be plotted.
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{p 4 4 2}
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Note: The new variables will contain data for the first k observations
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in the dataset, where k is 11 if not specified with the {cmd: ncases()}
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option or if not determined by the {cmd:gap} option.
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{title: Options}
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{p 4 8 2}
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{cmd:from()} and {cmd:to()} specify the values over which varname
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should vary when calculating predicted values. The defaults are the
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observed minimum and maximum values.
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{p 4 8 2}
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{cmd:generate()} is up to five letters to name the created variables.
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By changing the name you can run -prgen- repeatedly to compute predictions
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with variables held at various values. It is best to chose a name that is
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different from the beginning letters of variables in your data set.
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This is required.
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{p 4 8 2}
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{cmd:ci} indicates that you want to generate confidence intervals
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corresponding to the predictions made by {cmd:prgen}.
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{p 4 8 2}
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{cmd:marginal} indicates that you want to generate a variable
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containing the marginal change in the outcome relative to varname,
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holding all other variables constant.
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{p 4 8 2}
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{cmd:conditional} indicates that you want to generate conditional
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predictions rather than unconditional predictions for {cmd:ztp} and
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{cmd:ztnb} models.
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{p 4 8 2}
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{cmd:ncases} is the number of predicted values computed as varname
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varies from the start value to the end value. If {cmd:Ncases} is not
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specified, 11 points are generated.
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{p 4 8 2}
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{cmd:gap} is an alternative to {cmd:ncases}. You specify the gap or
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size between tic marks and {cmd:prgen} determines if the specified
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value divides evenly into the from-to range. If it does, {cmd:prgen}
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determines the appropriate value for {cmd:ncases}.
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{p 4 8 2}
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{cmd:x()} sets the values of independent variables for calculating
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predicted values. The list must alternate variable names and values.
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The values may be either numeric values or can be mean, median, min, max,
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previous, upper, or lower. The latter cannot be used if rest()
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specifies a group summary statistic (e.g., grmean).
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{p 4 8 2}
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{cmd:rest()} sets the independent variables not specified in x() to
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their {cmd:mean} (default), {cmd:minimum}, {cmd:maximum},
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{cmd:median} when calculating predicted values.{cmd:grmean} sets these
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independent variables to the mean conditional on the variables and
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values specified in x(); {cmd:grmedian}, {cmd:grmax}, and {cmd:grmin}
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can also be used. If {cmd:prvalue} has already been run after the last
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estimate, {cmd:previous} will set unspecified variables to their prior values.
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For models other than mlogit, {cmd:upper}and {cmd:lower} can be used to set
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independent variables to their minimum or maximum depending on which will yield
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the upper or lower extreme predicted value.
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{p 4 8 2}
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{cmd:maxcnt()} sets the maximum count for which variables are generated
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for count models. The value must be an integer between 0 and 30;
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the default is 9.
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{p 4 8 2}
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{cmd:all} specifies that any calculations of means, medians, etc.,
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should use the entire sample instead of the sample used to estimate
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the model.
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{p 4 8 2}
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{cmd:brief} and {cmd:nobase} suppress the base values of x in the output.
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{p 4 8 2}
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{cmd:nolabel} uses values rather than value labels in output.
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{p 4 8 2}
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{cmd:noisily} indicates that you want to see the output from
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{cmd:prvalue}that was was used to generate the predicted values.
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{p 4 8 2}
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{it:prvalue_options} control the calculation of confidence intervals;
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see {help prvalue} for details about these options.
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{title:Models and Predictions - * is the prefix}
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all models:
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*x: value of x
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logit & probit:
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Predicted probability of each outcome: *p0, *p1
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ologit, oprobit
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Predicted probabilities: *p#1,*p#2,... where #1,#2,... are values of
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the outcome variable.
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Cumulative probabilities: *s#1,*s#2,... where #1,#2,... are values
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of the outcome variable. *s#k is the probability of all
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categories up to or equal to #k.
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mlogit:
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Predicted probabilities: *p#1,*p#2,... where #1,#2,... are values of
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the outcome variable.
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poisson & nbreg:
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Predicted rate: *mu;
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Predicted probabilities: *p0, *p1... where 0, 1, are counts
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Cumulative probabilities: *s0, *s1... where 0, 1 are counts.
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The cumulative probability of a given count is probability of
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observing count less than or equal to that count.
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regress, tobit, cnreg, intreg
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Predicted xb: *xb
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{title: Examples}
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{p 4 4 2}
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To compute predicted values and confidencen intervals from an ordered probit
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where warm has four categories SD, D, A and SA:
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{p 4 8 2}{cmd:.oprobit warm yr89 male white age ed prst}
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{p 4 8 2}{cmd:.prgen age, f(20) t(80) gen(mn) ci delta}
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{p 4 8 2}{cmd:.prgen age, x(male=0) f(20) t(80) gen(fem)}
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{p 4 8 2}{cmd:.prgen age, x(male=1) f(20) t(80) gen(mal)}
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{p 4 8 2}
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To plot the predicted probabilites for average males:
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{p 4 8 2}{cmd:.twoway connected malp1 malp2 malp3 malp4 malx}
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{hline}
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{p 2 4 2}Authors: J. Scott Long, Jeremy Freese & Jun Xu{p_end}
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{p 11 4 2}{browse www.indiana.edu/~jslsoc/spost.htm}{p_end}
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{p 11 4 2}spostsup@indiana.edu{p_end}
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