About LOINC | The {roinc} package | What does the package do? | Installation | Usage | Authentication | Retrieve LOINC metadata | Download LOINC primary artifact | Search LOINC database | LOINC terminology services | Code system | Value sets

About the Pandemic PACT Figshare repository | Figshare interface | Set a Figshare client | List outputs/assets | Download outputs/assets | Read the Pandemic PACT tracker dataset and data dictionary | Process the Pandemic PACT tracker dataset

Website data interface | Website data workflow | Download data available from website | Read the Pandemic PACT tracker dataset from the website | Process the Pandemic PACT tracker dataset from the website

Features of blocked weighted bootstrap | Posterior weighting through resampling | Development history | Advantages

Background: the global problem of inadequate access to water and sanitation for the urban poor | Water and Sanitation for the Urban Poor (WSUP) | Valid International | Background to the citywide surveys | WSUP information requirements and other survey design considerations | Survey design | Sample Universe | Sample frame | Sample Size | Stage 1 sampling | Sampling Stage 2

Data wrangling | Creating summaries | Working with date and time data | Data visualisation | Bar plots | Scatter plots | Time series | Distribution plots

About the bagyo data

Retrieving PPI tables | Retrieving poverty probabilities

The Importance of Measuring Poverty | Functionality of the PPI | Example | History, development, and management of the PPI

Processing and recoding data | Estimating indicators | Blocked weighted bootstrap | PROBIT estimator | Classic estimator | Creating charts | Reporting estimates | The RAM-OP workflow in R using pipe operators | Piped operation to get output estimates table | Piped operation to get output an HTML report

Bootstrap resampling without parallelisation | Using one parameter and 400 replicates | Using varying number of parameters and 400 replicates | Bootstrap resampling with parallelisation

Original bootstrapping workflow | Bootstrap resampling with bootBW() | Bootstrap estimation | Stratified bootstrap resampling | Alternative blocked weighted bootstrap function set | Bootstrap resampling with boot_bw()

Africa CDC vision and mission | Africa CDC values | Africa CDC Colours | Africa CDC Palettes | Tinted blue palette | Tinted plum palette | Tinted blue grey palette | Tinted amber palette | Tinted cyan palette | Tinted deep orange palette | Tinted purple palette | Tinted lime palette | Tinted mauve palette | Tinted pink palette | Tinted teal palette | Africa CDC sequential brewer palettes | Blues | Blue to green | Blue to purple | Green to blue | Purple to blue | Purple to blue to green | Yellow to green | Yellow to green to blue | Yellow to orange to red | Africa CDC divergent brewer palettes | Pink to yellow to green | Purple to green | Purple to orange | Red to blue | Red to yellow to blue | Red to yellow to green | Africa CDC qualitative palettes | Pastel set 1 | Pastel set 2 | Africa CDC ggplot2 theme | Africa CDC light theme | Africa CDC dark theme

GNC colours | GNC palettes | Tinted green palette | Tinted grey palette | Tinted sage palette | Tinted dark green palette | Tinted lime palette | Tinted aqua green palette | Tinted cyan palette | Tinted blue palette | Tinted orange palette | Tinted moss green palette | Tinted gold palette | GNC ggplot2 theme

NHS colours | Core colours | Level 1: Blue tones | Level 2: Neutrals | Level 3: Support Greens | Level 4: Highlights | NHS sequential brewer palettes | Blues | Blue to green | Blue to purple | Green to blue | Greens | Greys | Purple to blue | Purple to blue to green | Purple to red | Red to purple | Reds | Yellow to green | Yellow to green to blue | Yellow to orange to red | NHS divergent brewer palettes | Pink to yellow to green | Purple to green | Purple to orange | Red to blue | Red to grey | Red to yellow to blue | Red to yellow to green | Africa CDC qualitative palettes | Pastel set 1 | Dark | NHS ggplot2 theme

UNICEF colours | UNICEF ggplot2 theme

World Bank Colours | World Bank Palettes | Bright palette | Neutral palette | Tinted bright orange palette | Tinted bright yellow palette | Tinted bright red palette | Tinted light orange palette | Tinted bright aqua palette | Tinted bright green palette | Tinted bright purple palette | Tinted light aqua palette | Tinted dark red palette | Tinted dark orange palette | Tinted brown palette | Tinted dark purple palette | Tinted dark aqua palette | Tinted dark green palette | World Bank ggplot2 theme

Classifying coverage

Objectives | Mechanics | Test parameters | Test organisation and requirements | Timeframe | Steps in carrying out the standardisation test

Intra-observer TEM for two measurements, and inter-observer TEM involving two measurers | Inter-observer TEM with more than two observers | Relative TEM | Total TEM for two observers and two measurements per observer | Total TEM for three observers and two measurements per observer | Relative total TEM | Coefficient of Reliability (R)

What does anthrocheckr do? | Installation | Usage

What does squeacr do? | Installation | Usage | Calculating CMAM programme performance metrics | CMAM programme length-of-stay | CMAM programme coverage

What does {pactr} do? | Why develop {pactr}?

Key Features of the ICD | ICD and Cause-of-Death reporting | Standardisation | Comparability | Data Aggregation and Analysis | Quality of Healthcare | Legal and Administrative Use | Example of ICD in Cause-of-Death Reporting

Code structure | Cause-of-death code structure checks for ICD-10 version | Cause-of-death code structure checks for ICD-11 version | Ill-defined cause-of-death codes | Ill-defined codes for ICD_10 and ICD-11 | Checks for ill-defined cause-of-death codes | Unlikely cause-of-death codes | Unlikely cause-of-death codes for ICD-10 and ICD-11 | Checks for unlikely cause-of-death codes | Cause-of-death code not appropriate for sex | Male-specific cause-of-death codes | Female-specific cause-of-death codes | Checks for sex-specific cause-of-death codes | Cause-of-death codes not appropriate for age | Neonate-specific cause-of-death codes | Child-specific cause-of-death codes | Checks for age-specific cause-of-death codes

Workflows for cause-of-death data processing and data quality checks using codeditr | Perform checks on existing input data for CoDEdit tool | Structure raw cause-of-death data for input into CoDEdit tool | Perform all checks on cause-of-death data | Perform specific check types on cause-of-death data

Oxford theme for forestploter package | Using Oxford heritage forest plot theme | Using Oxford contemporary forest plot theme | Using Oxford celebratory forest plot theme | Using Oxford corporate forest plot theme | Using Oxford innovative forest plot theme

Correcting serum haemoglobin | References

Classifying inflammation based on CRP or AGP only | Classifying inflammation based on both CRP and AGP | References

School age children | Pregnant women | Lactating women and children under 2 years of age | References

Correcting serum ferritin | References

Core fonts | Roboto | Noto Serif | Complementary display fonts | Marcellus | Monserrat | Noto Serif Display | Bebas Neue | Phudu | Checking availability of core fonts and complementary display fonts | Usage of Oxford fonts in the oxthema package | Ensuring that Oxford fonts show appropriately | Set RStudio graphics device to AGG | Making fonts work with .Rmd and .qmd files

Oxford theme palettes for use in plotting | Bar plot | Scatter plot | Plotting maps using Oxford palettes | Sequential palette | Divergent palette

Heritage | Contemporary | Celebratory | Corporate | Innovative

Calculating z-scores using the legacy functions | Calculating z-score for each of the three anthropometric indices for a single child | Calculating z-score for each of the three anthropometric indices for a cohort or sample of children | Calculating z-scores for all of the three anthropometric indices in one function

Introduction

Getting the z-score of a single child | Getting the z-score of a cohort of children