index.qmd

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)

library(fontawesome)
library(knitr)
library(kableExtra)
library(dplyr)
library(hexSticker)
library(ggplot2)
library(shiny)
library(quartoExtra) #devtools::install_github("debruine/quartoExtra")

options(kableExtra.html.bsTable = T)

quotes <- c(
"Essentially, all models are wrong, but some are useful. —George E.P. Box, British statistician",
"You can’t use up creativity. The more you use, the more you have. —Mary Angelou, American poet, singer, memoirist, and civil rights activist",
"A trend is a trend is a trend. But the question is, will it bend? Will it alter its course through some unforeseen force and come to a premature end? —Alexander Cairncross, British Economist",
"The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform. —Ada Lovelace, English mathematician and writer",
"Draw your assumptions before your conclusions. —Miguel Hernán, Spanish-American physician and epidemiologist",
"Statistics is the grammer of Science. —Karl Pearson, English statistician",
"Science and everyday life cannot and should not be seperated. —Rosalind Franklin, English chemist ",
"There are three kinds of lies - lies, damned lies and statistics. —Mark Twain, American writer",
"He uses statistics as a drunken man uses lamp posts – for support rather than for illumination. —Andrew Lang, Scottish writer",
"Know how to learn. Then, want to learn. —Katherine Johnson, American mathematician and NASA space scientist",
"I was taught that the way of progress was neither swift nor easy. —Marie Curie, French-Polish physicist",
"It's the inspired student that continues to learn on their own. That's what separates the real achievers in the world from those who pedal along, finishing assignments. —Neil deGrasse Tyson, American astrophysicist, author, and science communicator",
"If you start wielding a hammer, then all your problems look like nails. And maybe they’re not. —Neil deGrasse Tyson, American astrophysicist, author, and science communicator",
"Not everything that can be counted counts, and not everything that counts can be counted. —Albert Einstein, German-American theoretical physicist",
"One of the first things taught in introductory statistics textbooks is that correlation is not causation. It is also one of the first things forgotten. —Thomas Sowell, American Economist"
)


```


::: light-mode
![](images/light-mode.png)
:::

::: dark-mode
![](images/dark-mode.png)
:::


> `r sample(quotes, 1)`

# Course schedule

```{r}
#| column: body

firstDay <- as.Date("20230529", format = "%Y%m%d")
startDays <- format(firstDay + seq(0,69, 7), "%a %d %B")

topic <- c(
'Directed Acyclic Graphs (DAGs)',
'Matching for causal inference from observational data',
'Multilevel modelling I (Introduction)',
'Multilevel modelling II (Beyond the basics)',
'Multilevel modelling III (Repeated measures analysis)',
'Reading week',
'Time series analysis',
'Interrupted time series analysis',
'Missing data and multiple imputation',
'Presenting and summarising model results'
)

tuteOnline <- paste('4-6pm', format(firstDay+1 + seq(0,69,7), '%a %d %b'))
tuteOnline[6] <- 'No tutorial'

# tuteF2F <- paste('10-1pm', format(firstDay+3 + seq(0,69,7), '%a %d %b'))
# tuteF2F[6] <- 'No tutorial'

learnrLinks <- c(
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/dags/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/matching/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/multilevel-modelling-i/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/multilevel-modelling-ii/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/growth-curve-modelling/' target='_blank'></a>",
  "",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/time-series-analysis/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/interrupted-time-series/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/presenting-results/' target='_blank'></a>",
  "<a class='fa fa-code' href='https://cbdrh.shinyapps.io/multiple-imputation/' target='_blank'></a>"
)

videos <- c(
  "<a class='fa-brands fa-youtube' href='recordings.html#week-1.-directed-acyclic-graphs-dags'></a>",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-2.-matching-for-causal-inference-from-observational-data'></a>",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-3.-multilevel-modelling-i-introduction'></a>",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-4.-multilevel-modelling-ii-beyond-the-basics'></a>",
  "",
  "",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-7.-time-series-analysis'></a>",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-8.-interrupted-time-series-analysis'></a>",
    "<a class='fa-brands fa-youtube' href='recordings.html#week-9.-presenting-and-summarising-model-results'></a>",
  "<a class='fa-brands fa-youtube' href='recordings.html#week-10.-missing-data-and-multiple-imputation'></a>"
)

slides <- c(
  "<a class='fa fa-laptop' href='slides-dags.html' target='_blank'></a>",
  # "<a class='fa fa-laptop' href='slides-psm.html' target='_blank'></a>",
  # "<a class='fa fa-laptop' href='slides-mlm1.html' target='_blank'></a>",
  # "<a class='fa fa-laptop' href='slides-mlm2.html' target='_blank'></a>",
  # "<a class='fa fa-laptop' href='slides-mlm3.html' target='_blank'></a>",
  # "<a class='fa fa-clock' href='https://giphy.com/embed/XIqCQx02E1U9W' target='_blank'></a>",
  # "<a class='fa fa-file-pdf' href='slides-tsa.pdf' target='_blank'></a>",
  # "<a class='fa fa-file-pdf' href='slides-its.pdf' target='_blank'></a> 
  # <a class='fa fa-file-code' href='assets/timeseries-rough-code.R' target='_blank'></a> <br>
  # ",
  # "<a class='fa fa-file-pdf' href='slides-pres.pdf' target='_blank'></a>",
  # "<a class='fa fa-file-pdf' href='slides-mi.pdf' target='_blank'></a>",
  rep("<a class='fa fa-clock' href='https://giphy.com/embed/aCAzXzUR8GmDC' target='_blank'></a>", 9)
)
slides[6] <- ""


recordings <- c(
  # "<a class='fa-brands fa-youtube' href='https://unsw-my.sharepoint.com/:v:/g/personal/z3509778_ad_unsw_edu_au/EdfCF8-ZMtJEpx1Mr8tzEqEB-67ZG4dKor_85-d0Ga2XEA' target='_blank'></a>",
  #   "<a class='fa-brands fa-youtube' href='https://unsw-my.sharepoint.com/:v:/g/personal/z3509778_ad_unsw_edu_au/ERA2KnJbvVJEvQ6HB2TkL8MBlwy3OAQORSAc9cJzr9IWUA' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw-my.sharepoint.com/:v:/g/personal/z3509778_ad_unsw_edu_au/EQPQ-gWZLOdLsZ6IYP6fYl0BU-p38MCfB6TzlBQ7nNyOqg' target='_blank'></a>",
  #     "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/HDAT9700%20weekly%20online%20tutorials-20220928_170822-Meeting%20Recording.mp4?web=1' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/HDAT9700%20weekly%20online%20tutorials-20220928_183631-Meeting%20Recording.mp4?web=1' target='_blank'></a>",
  #       "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/EfZe7A-J0qJKgJAw3SJmx7MBzGqflkW8LbYlF_8P0h8EZQ?e=ORbMC6' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/ERIRTm4Zmz1BngDIiIrwWS0BpR0dpGQ3e_cOKj2znC4igA?e=ei9nFS' target='_blank'></a>",
  #   "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/HDAT9700%20weekly%20online%20tutorials-20221012_171330-Meeting%20Recording.mp4?web=1' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/Online%20Tutorial-20221012_183412-Meeting%20Recording.mp4?web=1' target='_blank'></a>",
  # "Reading week",
  # "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/EeqKc1Xa8U9DuBI2igJ5ZIsBOzi5WIUcRoeeHmhJI88SYA?e=DLlvj6' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/EYdH3FYc4zJLoHDKs4imUGIB1tqHbuO3ySRDJVmXWLtDxA?e=QaHqwd' target='_blank'></a>",
  #   "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/Meeting%20in%20_Online%20Tutorial_-20221102_170903-Meeting%20Recording.mp4?web=1'  target='_blank'></a><br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/sites/CLS-HDAT9700_T3_5229_Combine/Shared%20Documents/Online%20Tutorial/Recordings/Meeting%20in%20_Online%20Tutorial_-20221102_180247-Meeting%20Recording.mp4?web=1' target='_blank'></a><br><div style='font-size:0.5em; color:grey;text-align:left;'>*Note the 2nd recording got cut off; please see worked examples in learnr tute</div>",
  #     "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/EVEuBbLPLMdDjYRzNR01y1YBze0GEdZZEv7LLikRqy0jMA?e=1a9IMe' target='_blank'></a>",
  #     "<a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/Eb40Til4jGNCgfs3lZbJvHwBePY6HB9pM0szq_wEMIJWiQ?e=zDOyh7' target='_blank'></a> <br>
  #    <a class='fa-brands fa-youtube' href='https://unsw.sharepoint.com/:v:/s/CLS-HDAT9700_T3_5229_Combine/EXL-3VUOVLNNjoFw_kVgDAgBVexsYh-m5j4PW9XUGJrSQQ?e=mFgw7f' target='_blank'></a>",
     rep("<a class='fa fa-clock' href='https://giphy.com/embed/aCAzXzUR8GmDC' target='_blank'></a>", 10)
)
recordings[6] <- ""

#
df <-
  data.frame(
    Week = paste("Week", 1:10),
    Start <- startDays,
    Topic = topic,
    Link = learnrLinks,
    videos=videos,
    tuteOnline = tuteOnline,
    # tuteF2F = tuteF2F,
    slides = slides,
    recordings = recordings
  )

kbl(df,
    escape = FALSE,
    align = c('l', 'l', 'l', 'c', 'c', 'l', 'c', 'c'),
    col.names = c("Week", "Week starting", "Topic", 'learnr tutorial', 'Videos', 'Online tutorial', 'Tutorial slides', "Tutorial recordings")
    ) %>%
  kable_styling(bootstrap_options = "hover")

```

<aside>

<div class=myAside>

<hr class=myHr>

<p>Links to slides and recordings will be posted here throughout the course</p>

</div>

</aside>

<br>

# Course outline

You can read the course outline [here](course-outline.html). Click here to download a pdf copy of the latest course outline: <a class='fa fa-file-pdf' href='assets/august-2022-hdat9700-course-outline.pdf' target='_blank'></a>

Access the course overview slides [here](slides-overview.html){target="_blank"}.

<br>

<!-- # In-person tutorials -->

<!-- The weekly in-person tutorials take place in the [Mathews Building Room 105](https://www.learningenvironments.unsw.edu.au/physical-spaces/mathews-building/k-f23-105-mathews-105){target="_blank"}. -->

<!-- <iframe src="https://www.google.com/maps/d/embed?mid=1xn9fg2_H2CDwCveLYrvZThC0RcBvKc4&amp;ehbc=2E312F" width="640" height="480"> -->

<!-- </iframe> -->

# Teams space

::: container
::: left20
![](https://upload.wikimedia.org/wikipedia/commons/c/c9/Microsoft_Office_Teams_(2018%E2%80%93present).svg){width="60%"}
:::

::: right80
Discussions, questions and online tutorials will be hosted in the course Teams Space which you can access [here](https://teams.microsoft.com).
:::
:::

<br>

# The tutorials R package

The learnr tutorials for this course can be accessed through the links above but it is ideal to have a local copy that you can work on in the RStudio environment without the need for internet access.

The tutorials are shipped in the package `hdat9700tutorials`. To install this package you can enter the following code at the console:

```{r, eval = FALSE, echo = TRUE}
devtools::install_github("CBDRH/hdat9700")
```

You may get prompted to update some packages. You can chose to ignore this by selecting option 3 (None).

![](images/package-update.png){width="95%"}

If you choose to update packages, you may subsequently be asked if you want to install binary or source versions. Source versions require special tools to compile which you may not have configured, so you should choose to install the binary version, i.e. if prompted *Do you want to install from sources the packages which need compilation?* enter n for 'No'.

The package installation can occasionally fail, usually if there is a dependency that is not installed or has an outdated version. If you get an error message relating to a package, try installing that package first and then try again. If there are still issues, don't worry, just [drop an email to the course convenor](contact.html).

<br>

# Assessment

```{r}

df <- data.frame(

  task <- c("Assessment 1A", "Assessment 1B", "Assessment 1C", "Assessment 2"),
  topic <- c("DAGs and Matching", "Multilevel modelling", "Time series analysis", "Short report"),
  release <- format(c(firstDay + 9, firstDay + 23, firstDay + 44, firstDay + 51), "%a %d %b"),
  weight <- c("50%/3", "50%/3", "50%/3", "50%"),
  due <- paste("9am,", format(c(firstDay + 21, firstDay + 42, firstDay + 63, firstDay + 77), "%a %d %b")),
  link <- c(
    # "<a class='bi bi-github' href='https://classroom.github.com/a/lFmDT6R2' target='_blank'></a>",
    # "<a class='bi bi-github' href='https://classroom.github.com/a/BEP-71S-' target='_blank'></a>",
    # "<a class='bi bi-github' href='https://classroom.github.com/a/73Y5TB9y' target='_blank'></a>",
    #     "<a class='bi bi-github' href='https://classroom.github.com/a/WmRzsCVt' target='_blank'></a>",
    rep("<a class='fa fa-clock' href='https://media.giphy.com/media/XIqCQx02E1U9W/giphy.gif' target='_blank'></a>", 4)
  ),
  solution <- c(
    # "<a class='fa fa-lightbulb' href='https://github.com/' target='_blank'></a>",
    rep("<a class='fa fa-clock' href='https://media.giphy.com/media/XIqCQx02E1U9W/giphy.gif' target='_blank'></a>", 3), "")
  #
)

kbl(df,
    escape = FALSE,
    align = c('l', 'l', 'l', 'l', 'l', 'c', 'c'),
    col.names = c("Assessment", "Topic", "Release date", "Weight", "Due date", "Repo link", "Solution")
    ) %>%
  kable_styling(bootstrap_options = "hover")


```

<aside>

<hr class=myHr>

::: myAside
<p>

Click the link to clone a personal copy of the GitHub repo for each assessment.

To access the solution you need to be a member of the GitHub Team. Reach out if you can't access.

</p>
:::

</aside>

<br>

# Readings and resources

Readings can also be accessed through the UNSW Library Leganto list [here](https://unsw.alma.exlibrisgroup.com/leganto/public/61UNSW_INST/lists/50903387710001731?auth=SAML).

## Week 1. Directed Acyclic Graphs (DAGs)

```{r}

reading = c(
  "Miguel A. Hernán, John Hsu & Brian Healy (2019) A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks, Chance, 32(1), 42-49",
  "Austin, Anna E., Tania A. Desrosiers, and Meghan E. Shanahan. Directed Acyclic Graphs: An under-utilized tool for child maltreatment research. Child Abuse & Neglect 91 (2019): 78-87",
  "Shmueli, Galit. To Explain or to Predict? Statist. Sci. 25 (2010), no. 3, 289-310",
  "The importance of being clear about your question & using that to drive your methods, a tweetorial by epidemiologist Dr Ellie Murray from Boston University School of Public Health.",
  "dagitty.net A great website explaining DAGs and related topics, with built-in applets to test your knowledge",
  "An excellent YouTube video series on Causality and DAGs presented by Assistant Professor Nick Huntington-Klein from Seattle University. This is a series of 14 videos that starts from the very basics of causal thinking with DAGs"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://www.tandfonline.com/doi/full/10.1080/09332480.2019.1579578' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://doi.org/10.1016/j.chiabu.2019.02.011' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.stat.berkeley.edu/~aldous/157/Papers/shmueli.pdf' target='_blank'></a> <a class='fa-brands fa-youtube' href='https://www.youtube.com/watch?v=vWH_HNfQVRI&t=1s' target='_blank'></a>",
  "<a class='fa-brands fa-twitter' fill = 'lightblue' href='https://twitter.com/EpiEllie/status/1214641734900224003' target='_blank'></a>",
  "<a class='fa fa-laptop' href='http://www.dagitty.net/' target='_blank'></a>",
  "<a class='fab fa-youtube' href='https://www.youtube.com/playlist?list=PLcTBLulJV_AKmUTH-nUsxxFyRQoWnUzxU' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = "hover") %>%
  kableExtra::group_rows(start_row = 1, end_row = 2, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 3, end_row = 6, group_label = "Other resources")

```

<aside>

<hr class=myHr>

::: myAside
<p>

You should prioritise the core readings each week.

Note that some of the links below will require you to be logged in to your UNSW library account to access, or alternatively use the [UNSW Library Leganto list](https://unsw.alma.exlibrisgroup.com/leganto/public/61UNSW_INST/lists/50903387710001731?auth=SAML).

</p>
:::

</aside>

## Week 2. Matching for causal inference from observational data

```{r}

reading = c(
  "Why Propensity Scores Should Not Be Used For Matching presented by Professor Gary King from Harvard University",
  "Daniel Ho, Kosuke Imai, Gary King and Elizabeth Stuart (2007) Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Political Analysis 15 199-236",
  "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference by Daniel E. Ho, Kosuke Imai, Gary King and Elizabeth A. Stuart, Journal of Statistical Software (2011) 42(8), 1-28. pdf",
  "Does obesity shorten life? The importance of well-defined interventions to answer causal questions by MA Hernán amd SL Taubman, International Journal of Obesity (2008) Volume 32, pages S8–S14",
  "Causal Inference: What If by Miguel A. Hernán, James M. Robins, Boca Raton: Chapman & Hall/CRC (1st Edition 2020) (Chapter 15 discusses Propensity Score appliactions)"
)

links <- c(
  "<a class='fa-brands fa-youtube' href='https://youtu.be/rBv39pK1iEs?t=87' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://gking.harvard.edu/files/matchp.pdf' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.jstatsoft.org/index.php/jss/article/view/v042i08/505' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.nature.com/articles/ijo200882' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1268/2021/03/ciwhatif_hernanrobins_30mar21.pdf' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 1, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 2, end_row = 5, group_label = "Other resources")

```

## Week 3. Multilevel modelling I (Introduction)

```{r}

reading = c(
  "Murder, muddled thinking and multilevel modelling by Martin Cartwright, Gemma Traviss and Andrew Blance, The Psychologist (2012) Vol 25 No 9",
  "A Primer on Using Multilevel Models in Clinical and Experimental Psychopathology Research by Andy Field and Daniel Wright, Journal of Experimental Psychopathology (2011) 2(2)",
  "A visual explanation of multilevel modelling by Michael Freeman, a faculty member at the University of Washington Information School",
  "Blance (2012) Chapter 5 Multilevel Modelling in Modern Methods for Epidemiology by Yu-Kang and Greenwood (eds) (also available in hard copy and e-Book format through the UNSW library)",
  "Centre for Multilvel Modelling, University of Bristol explanatory videos",
  "Centre for Multilvel Modelling, University of Bristol online course"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://openaccess.city.ac.uk/id/eprint/14840/' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://journals.sagepub.com/doi/abs/10.5127/jep.013711' target='_blank'></a>",
  "<a class='fa fa-laptop' href='http://mfviz.com/hierarchical-models/' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://link.springer.com/chapter/10.1007/978-94-007-3024-3_5' target='_blank'></a>",
  "<a class='fa-brands fa-youtube' href='http://www.bristol.ac.uk/cmm/learning/videos/' target='_blank'></a>",
  "<a class='fa fa-laptop' href='http://www.bristol.ac.uk/cmm/learning/online-course/' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 3, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 4, end_row = 6, group_label = "Other resources")

```

## Week 4. Multilevel Modelling II (Beyond the basics)

```{r}

reading = c(
  "Hanly, Savva, Clifford & Whelan (2014). Variation in Incentive Effects across Neighbourhoods. Survey Research Methods, 8(1)",
  "Andy Field, Jeremy Miles, Zoë Field (2012) Discovering statistics using R, Chapter 19 (also available in hardcopy through the UNSW library)"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://ojs.ub.uni-konstanz.de/srm/article/view/5485/5336' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://unsw.alma.exlibrisgroup.com/leganto/readinglist/citation/50903548670001731?institute=61UNSW_INST&auth=SAML' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 2, group_label = "Core readings")

```

## Week 5. Multilevel modelling III (Repeated measures analysis)

```{r}

reading = c(
  "Curran, Obeidat, and Losardo (2010) Twelve Frequently Asked Questions About Growth Curve Modeling J Cogn Dev 11(2)",
  "Galecki, AT., Burzykowski, T. (2013) Linear Mixed-Effects Models Using R: A Step-By-Step Approach. Springer",
  "Magnusson, K. Using R and lme/lmer to fit different two- and three-level longitudinal models",
  "University of Twente. Growth Modeling. Slide presentation"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://www.tandfonline.com/doi/pdf/10.1080/15248371003699969' target='_blank'></a>",
  "",
  "<a class='fa fa-laptop' href='http://rpsychologist.com/r-guide-longitudinal-lme-lmer' target='_blank'></a>",
  "<a class='fa fa-laptop' href='https://slideplayer.com/slide/13828326/' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 1, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 2, end_row = 4, group_label = "Other resources")

```

## Week 7. Time Series Analysis

```{r}

reading = c(
  "Zeger et al. On Time Series Analysis of Public Health and Biomedical Data. Annuals Reviews of Public Health 2005",
  "Bhaskaran et al. Time series regression studies in environmental epidemiology. International Journal of Epidemiology 2013",
  "Time series analysis and its applications: with R examples (Chapters 1-3) by Robert H Shumway and David S Stoffer online (or through the UNSW library).",
  "Rob J Hyndman and George Athanasopoulos (Monash University), Forecasting: Principles and Practice")

links <- c(
  "<a class='fa fa-file-pdf' href='https://www.annualreviews.org/doi/full/10.1146/annurev.publhealth.26.021304.144517' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://academic.oup.com/ije/article/42/4/1187/657875' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.stat.pitt.edu/stoffer/tsa4/' target='_blank'></a>",
  "<a class='fa fa-laptop' href='https://otexts.com/fpp2/' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 2, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 3, end_row = 4, group_label = "Other resources")

```

## Week 8. Interrupted Time Series Analysis

```{r}

reading = c(
  "Bernal et al. Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology 2016",
  "Schaffer et al. Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions BMC Medical Research Methodology 2021",
  "Soumerai et al. How Do You Know Which Health Care Effectiveness Research You Can Trust? A Guide to Study Design for the Perplexed. Prev Chronic Dis 2015; 12:150187",
  "Jandoc et al. Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations. J Clin Epidemiol 2015;68(8):950-6. (This article has useful guidance for the reporting of interrupted time series analysis methods.)",
  "Lopez Bernal et al. A methodological framework for model selection in interrupted time series studies. J Clin Epidemiol 2018; 103:82-91", "Lopez Bernal et al. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol 2018; 0(0):1-12", "Lagarde. How to do (or not to do): Assessing the impact of a policy change with routine longitudinal data. Health Policy Planning 2012; 27(1):76-83")

links <- c(
  "<a class='fa fa-file-pdf' href='https://doi.org/10.1093/ije/dyw098' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-021-01235-8' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='http://dx.doi.org/10.5888/pcd12.150187' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.sciencedirect.com/science/article/pii/S0895435615001237' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://www.sciencedirect.com/science/article/abs/pii/S0895435617314117' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://academic.oup.com/ije/article/47/6/2082/5049576' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://doi.org/10.1093/heapol/czr004' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 2, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 3, end_row = 7, group_label = "Other resources")

```

## Week 9. Presenting and summarising model results

```{r}

reading = c(
  "Rothman, K. J. (2014). Six persistent research misconceptions. Journal of General Internal Medicine, 29 (7), 1060-1064.",
  "Interpreting and presenting statistical results, video lecture form Professor Gary King online (Check out from the start until about 11m 30s)"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061362/' target='_blank'></a>",
  "<a class='fa-brands fa-youtube' href='https://www.youtube.com/watch?v=gbokhfMdfE8&list=PLmpS1iNDaUFtat0QiqXZhlsAgseWtJ1Kk&index=11&t=0s' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 1, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 2, end_row = 2, group_label = "Other resources")

```

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## Week 10. Missing Data and Multiple Imputation

```{r}

reading = c(
  "Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls, Jonathan AC Sterne, Ian R White, John B Carlin, Michael Spratt, Patrick Royston, Michael G Kenward, Angela M Wood, James R Carpenter BMJ 2009",
  "Flexible Imputation of Missing Data by Stef Van Buuren"
)

links <- c(
  "<a class='fa fa-file-pdf' href='https://doi.org/10.1136/bmj.b2393' target='_blank'></a>",
  "<a class='fa fa-file-pdf' href='https://stefvanbuuren.name/fimd/' target='_blank'></a>"
)


df <- data.frame(
  reading = reading,
  links = links
)


kbl(df, escape = FALSE,
    align = c('l', 'c'),
    col.names = NULL) %>%
  kable_styling(bootstrap_options = c("hover")) %>%
  kableExtra::group_rows(start_row = 1, end_row = 1, group_label = "Core readings") %>%
  kableExtra::group_rows(start_row = 2, end_row = 2, group_label = "Other resources")

```