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https://github.com/maraab23/seqquality

R package computing a generalized version of the sequence quality index
https://github.com/maraab23/seqquality

Last synced: 19 days ago
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R package computing a generalized version of the sequence quality index

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README 

        
---

title: "Sequence Quality Index"

output: 

  github_document:

    pandoc_args: --webtex

---



```{r setup, include=FALSE}

knitr::opts_chunk$set(echo = TRUE)

library(seqquality)

library(tidyverse)

library(TraMineR)

```



![Status](https://img.shields.io/badge/status-early%20release-yellowgreen)

![Version](https://img.shields.io/badge/version-0.1.0-blue)



**[Marcel Raab](https://marcelraab.de/)**



R/seqquality is an [R](https://www.r-project.org) package comprising only a single function which computes a generalized version of the sequence quality index proposed by *Manzoni and Mooi-Reci (2018)*. The index is defined as 



$$

Q_{i}=\frac{\sum_{i=1}^{k}{q_{i}i^{w}_{i}}}{\sum_{i=1}^{k}{q_{max}i^{w }_{i}}}

$$



where $i$ indicates the position within the sequence and $k$ the total length of the sequence. $w$ is a weighting factor simultaneously affecting how strong the index reacts to (and recovers from) a change in state quality. $q_{i}$ is a weighting factor denoting the quality of a state at position $i$. The function normalizes $q_{i}$ to have values between 0 and 1. Therefore, $q_{max}=1$. If no quality vector is specified, the first state of the alphabet is coded 0, whereas the last state is coded 1. For the states in-between each step up the hierarchy increases the value of the vector by ${1}/{(l(A)-1)}$, with $l(A)$ indicating the length of the alphabet. This procedure was borrowed from the `seqprecstart`, a helper function used for the implementation of the sequence precarity index proposed by *Ritschard et al. (2018)*. 



The package can be installed using `install_github` from the `devtools` package:



```{r install, eval=FALSE}

install.packages("devtools")

library(devtools)

install_github("maraab23/seqquality")

library(seqquality)

```



## Examples



First, you need to load additional libraries and data to run the examples.



```{r examplePrep, eval=FALSE}

library(tidyverse)

library(TraMineR)



data(actcal)

# Define state sequence object

actcal.seq <- seqdef(actcal[,13:24])

```



```{r, include=FALSE}

data(actcal)

# Define state sequence object

actcal.seq <- seqdef(actcal[,13:24])

```



We use the `actcal` example data that come with the `TraMineR`package. This dataset comprises 2000 individual sequences of monthly activity statuses from January to December 2000 (type `?actcal` for getting more details). The sequence alphabet is defined as: 



- A = Full-time paid job (> 37 hours)

- B = Long part-time paid job (19-36 hours) 

- C = Short part-time paid job (1-18 hours) 

- D = Unemployed (no work) 



For illustration purposes we impose the following state quality hierarchy: $D long format)

fig.data <- qual.binary.tvar %>%

  mutate(Sequence = example.sps) %>%

  select(-weight) %>%

  pivot_longer(-Sequence, 

               names_to = "Position",

               values_to = "Sequence Quality") %>%

  mutate(Position = as.numeric(substring(Position, first = 3)))



# Plot the development of the sequence quality index

fig.data %>%

  ggplot(aes(x = Position, 

             y = `Sequence Quality`, 

             color = Sequence)) +

  geom_line(size=1) +

  theme_minimal() +

  theme(legend.position="bottom") +

  guides(col=guide_legend(nrow=2,byrow=TRUE)) 

```



## References



Manzoni, A., & Mooi-Reci, I. (2018). *Measuring Sequence Quality*. In G. Ritschard & M. Studer (Eds.), Sequence Analysis and Related Approaches (pp. 261–278). doi: 10.1007/978-3-319-95420-2_15



Ritschard, G., Bussi, M., & O’Reilly, J. (2018). *An Index of Precarity for Measuring Early Employment Insecurity*. In G. Ritschard & M. Studer (Eds.), Sequence Analysis and Related Approaches (pp. 279–295). doi: 10.1007/978-3-319-95420-2_16