General tools for exploratory process data analysis. Process data refers to the data describing participants' problem solving processes in computer-based assessments. It is often recorded in computer log files. This package a process dataset and functions for reading processes from a csv file, process manipulation, action sequence generators. It also implements two automatic feature extraction methods that compress the information stored in process data, which often has a nonstandard format, into standard numerical vectors. This package also provides recurrent neural network based models that relate response processes with other binary or scale variables of interest. The functions that involve training and evaluating neural networks are based on functions in keras.
ProcData organizes response processes as an object of class
Some functions are provided for summarizing and manipulating
summary.proc calculates summary statistics of a
remove_action removes actions and the corresponding timestamps
replace_action replaces an action by another action
combine_actions combines consecutive action into one action.
read.seqs reads response processes from a csv file.
seq_gen generates action sequences of an imaginery simulation-based item.
seq_gen2 generates action sequences according to a given probability
seq_gen3 generates action sequences according to a recurrent neural network.
seq2feature_mds extracts features from response processes by
seq2feature_seq2seq extracts features from response processes by
seq2feature_ngram extracts ngram features from response processes.
seqm fits a neural network model that relates response processes
with a response variable.
predict.seqm makes predictions from the models fitted by
Maintainer: Xueying Tang email@example.com
Susu Zhang firstname.lastname@example.org
Zhi Wang email@example.com
Jingchen Liu firstname.lastname@example.org
Zhiliang Ying email@example.com
Report bugs at https://github.com/xytangtang/ProcData/issues
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