| 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.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_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 | Respondent-Driven Sampling |
| 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 |
| [-method | indexing |
| [.rds.data.frame | indexing |
| [<--method | indexing |
| [<-.rds.data.frame | indexing |