# Articles by Analysis on StatsNotebook - Simple. Powerful. Reproducible.

### Age-period-cohort analysis

March 28, 2021 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Visit our Analysis section for other tutorials. Epidemiologists and social scientists often apply Age-Period-Cohort analysis to disentangle trends of social/health behvaiors int...
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### Robust regression

December 7, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Outliers and violations of distributional assumptions are common in many area of research. These issues might introduce substantial bias in the analysis and potentially lead to ...
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### IPTW with missing data

December 4, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. This is a follow-up tutorial built on our tutorial on inverse probability treatment weight. In this tutorial, we use the same example, but with some missing data in the dataset....
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### Inverse probability treatment weighting

December 4, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. In multiwave longitudinal study, the exposure is often time-varying. A time varying confounder is a time varying variable that is affected by previous exposures, and also affect...
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### Linear mixed model (Multilevel model)

October 19, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Data with multilevel (hierarchical) structure are common in many area of research. In our tutorial on moderation analysis, we examine the impact of increasing alcohol tax in Que...
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### Residual plots and assumption checking

October 15, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. A residual plot is an essential tool for checking the assumption of linearity and homoscedasticity. The following are examples of residual plots when (1) the assumptions are met...
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### Multiple Imputation

September 22, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Missing data is a norm rather than an exception in most areas of research. Excluding observations with missing data reduces statistical power and potentially introduces bias in ...
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### Causal Mediation Analysis

September 22, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Mediation analysis is a technique that examines the intermediate process by which the independent variable affects the dependent variable. For example, family intervention durin...
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### Moderation (Interaction) analysis using linear regression

September 21, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Assumed knowledge in this tutorial: Linear regression Moderation analysis is used to examine if the effect of an independent variable on the dependent variable is the same acros...
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### Descriptive statistics

September 19, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. This tutorial will give a short introduction on descriptive analysis using StatsNotebook. Descriptive statistics such as mean, standard deviation, median and interquartile range...
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### Linear regression with missing data

September 17, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. In many area of research, missing data is a norm rather than an exception. Dropping observations/ participants with missing data is usually not appropriate as it reduces statist...
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### Linear Regression

September 17, 2020 |

The tutorial is based on R and StatsNotebook, a graphical interface for R. Linear regression is a technique for examining the relationship between a dependent variable (outcome) and a set of independent variables (predictors). This tutorial demonstrate...
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