Respondent-Driven Sampling


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Documentation for package ‘RDS’ version 0.9-9

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$.control.list Named element accessor for ergm control lists
as.char converts to character with minimal loss of precision for numeric variables
as.rds.data.frame Coerces a data.frame object into an rds.data.frame object.
assert.valid.rds.data.frame Does various checks and throws errors if x is not a valid rds.data.frame
bootstrap.contingency.test Performs a bootstrap test of independance between two categorical variables
bootstrap.incidence Calculates incidence and bootstrap confidence intervals for immunoassay data collected with RDS
bottleneck.plot Bottleneck Plot
compute.weights Compute estimates of the sampling weights of the respondent's observations based on various estimators
control.list.accessor Named element accessor for ergm control lists
control.rds.estimates Auxiliary for Controlling RDS.bootstrap.intervals
convergence.plot Convergence Plots
count.transitions Counts the number or recruiter->recruitee transitions between different levels of the grouping variable.
cumulative.estimate Calculates estimates at each successive wave of the sampling process
differential.activity.estimates Differential Activity between groups
export.rds.interval.estimate Convert the output of print.rds.interval.estimate from a character data.frame to a numeric matrix
faux A Simulated RDS Data Set
fauxmadrona A Simulated RDS Data Set with no seed dependency
fauxmadrona.network A Simulated RDS Data Set with no seed dependency
fauxsycamore A Simulated RDS Data Set with extreme seed dependency
fauxsycamore.network A Simulated RDS Data Set with extreme seed dependency
fauxtime A Simulated RDS Data Set
get.h.hat Get Horvitz-Thompson estimator assuming inclusion probability proportional to the inverse of network.var (i.e. degree).
get.id Get the subject id
get.net.size Returns the network size of each subject (i.e. their degree).
get.number.of.recruits Calculates the number of (direct) recuits for each respondent.
get.population.size Returns the population size associated with the data.
get.recruitment.time Returns the recruitment time for each subject
get.rid Get recruiter id
get.seed.id Calculates the root seed id for each node of the recruitement tree.
get.seed.rid Gets the recruiter id associated with the seeds
get.stationary.distribution Markov chain statistionary distribution
get.wave Calculates the depth of the recruitment tree (i.e. the recruitment wave) at each node.
gile.ss.weights Weights using Giles SS estimator
has.recruitment.time RDS data.frame has recruitment time information
hcg.weights homophily configuration graph weights
homophily.estimates This function computes an estimate of the population homophily and the recruitment homophily based on a categorical variable.
impute.degree Imputes missing degree values
impute.visibility Estimates each person's personal visibility based on their self-reported degree and the number of their (direct) recruits. It uses the time the person was recruited as a factor in determining the number of recruits they produce.
impute.visibility_mle Estimates each person's personal visibility based on their self-reported degree and the number of their (direct) recruits. It uses the time the person was recruited as a factor in determining the number of recruits they produce.
is.rds.data.frame Is an instance of rds.data.frame
is.rds.interval.estimate Is an instance of rds.interval.estimate
is.rds.interval.estimate.list Is an instance of rds.interval.estimate.list This is a (typically time ordered) sequence of RDS estimates of a comparable quantity
LRT.trend Compute a test of trend in prevalences based on a likelihood-ratio statistic
LRT.trend.null Compute a test of trend in prevalences based on a likelihood-ratio statistic
LRT.trend.test Compute a test of trend in prevalences based on a likelihood-ratio statistic
LRT.value.trend Compute a test of trend in prevalences based on a likelihood-ratio statistic
MA.estimates MA Estimates
plot.rds.data.frame Diagnostic plots for the RDS recruitment process
print.differential.activity.estimate Prints an differential.activity.estimate object
print.pvalue.table Displays a pvalue.table
print.rds.contin.bootstrap Displays an rds.contin.bootstrap
print.rds.data.frame Displays an rds.data.frame
print.rds.interval.estimate Prints an 'rds.interval.estimate' object
print.summary.svyglm.RDS Summarizing Generalized Linear Model Fits with Odds Ratios
RDS.bootstrap.intervals RDS Bootstrap Interval Estimates
RDS.compare.proportions Compares the rates of two variables against one another.
RDS.compare.two.proportions Compares the rates of two variables against one another.
RDS.HCG.estimates Homophily Configuration Graph Estimates
RDS.I.estimates Compute RDS-I Estimates
rds.I.weights RDS-I weights
RDS.II.estimates RDS-II Estimates
rds.interval.estimate An object of class rds.interval.estimate
RDS.SS.estimates Gile's SS Estimates
rdssampleC Create RDS samples with given characteristics
read.rdsat Import data from the 'RDSAT' format as an 'rds.data.frame'
read.rdsobj Import data saved using write.rdsobj
reingold.tilford.plot Plots the recruitment network using the Reingold Tilford algorithm.
rid.from.coupons Determines the recruiter.id from recruitment coupon information
set.control.class Set the class of the control list
show.rds.data.frame Displays an rds.data.frame
summary.svyglm.RDS Summarizing Generalized Linear Model Fits with Odds Ratios for Survey Data
transition.counts.to.Markov.mle calculates the mle. i.e. the row proportions of the transition matrix
ult Extract or replace the *ult*imate (last) element of a vector or a list, or an element counting from the end.
vh.weights Volz-Heckathorn (RDS-II) weights
write.graphviz writes an rds.data.frame recruitment tree as a GraphViz file
write.netdraw Writes out the RDS tree in NetDraw format
write.rdsat Writes out the RDS tree in RDSAT format
write.rdsobj Export an rds.data.frame to file
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