From: A survey of statistics in three UK general practice journal

Category | Brief description |
---|---|

No statistical methods or descriptive statistics | No statistical content, or descriptive statistics only (e.g., percentages, means Standard deviations, standard errors, histograms |

Contingency tables | Chi-square tests, Fisher's test, McNemar's test |

Multiway tables | Mantel-Haenszel procedure, log-linear models |

Epidemiological studies | Relative risk, odds ratio, log odds, measures of association, sensitivity, specificity |

t-tests | One-sample, matched pair, and two sample t- tests |

Pearson correlation | Classic product-moment correlation |

Simple linear regression | Least-squares regression with one predictor and one response variable |

Multiple regression | Includes polynomial regression and stepwise regression |

Analysis of variance | Analysis of variance, analysis of covariance, and F-tests |

Multiple comparisons | Procedures for handling multiple inferences on same data sets (e.g., Bonferroni techniques, Scheffe's contrasts, Duncan's multiple range procedures, Newmann-Keuls procedure) |

Non-parametric tests | Sign test, Wilcoxon signed ranks test, Mann- Whitney test, Spearman's rho, Kendall's tau, test for trend |

Life table | Actuarial life table, Kaplan-Meier estimates of survival |

Regression for survival | Includes Cox regression and logistic regression |

Other survival analysis | Breslow's Kruskal Wallis, log rank, Cox model for comparing survival |

Adjustment & standardisation | Pertains to incidence rates and prevalence rates |

Sensitivity analysis | Examines sensitivity of outcome to small changes in assumptions |

Power | Loosely defined, includes use of the size of detectable (or useful) difference in determining sample size |

Transformation | Use of data transformation (e.g., logs) often in regression |

Cost-benefit analysis | The process of combining estimates of cost and health outcomes to compare policy alternatives |

Other | Anything not fitting the above headings includes cluster analysis, discriminant analysis, and some mathematical modelling |