Introduction to Medical Statistics 2024-25 PDF

Summary

This document introduces medical statistics and biostatistics, covering definitions, types of variables, data collection and analysis. The document explores the use and importance of statistics in the field of medicine, highlighting its role in research and generating hypotheses.

Full Transcript

Definitions - Data Medicine is essentially an empirical science  depends on observations and not on theories As a part of clinical practice or research we deal with many observations, which when systematically arranged, are called Data 20/8/2024 Adapted from Prof. Ali Nawa...

Definitions - Data Medicine is essentially an empirical science  depends on observations and not on theories As a part of clinical practice or research we deal with many observations, which when systematically arranged, are called Data 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 7 Definitions- Statistics The process of converting data into information requires a special approach called Statistics ‘Statistics’ means a measured or counted fact or piece of information, stated as a figure such as height of one person, birth weight of a baby, etc. 20 August 2024 Medical statistics Data Vs. Statistics (I) Data 20/8/2024 9 Data Vs. Statistics (II) Statistics 20/8/2024 10 Definitions- Statistics and Biostatistics Statistics Data collection, analysis, interpretation, dissemination, and presentation Medical Statistics The use of statistics in the field of medicine and science Biostatistics Statistics concerned with biological events 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 11 What Biostatistics Covers.. Biostatistics covers applications and contributions not only from health, medicines and, nutrition but also from fields such as genetics, biology, epidemiology, and many others It mainly consists of various steps like generation of hypothesis, collection of data, and application of statistical analysis 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 12 Why do we need Medical Statistics? Three reasons: 1. Basic requirement of medical research. 2. Update your medical knowledge. 3. Data management and treatment. 20 August 2024 Medical statistics Functions of Medical Statistics 1) Presentation of data in a definite form, as to translate the descriptive words (e.g. blood pressure, height, weight, temperature,..) to certain numbers 2) Presentation of data in a simple form, as complex data may be reduced to: averages, means 3) Comparison of health status of different localities, and in one locality at different times 4) Diagnosis of a health problem in the community 5) Evaluation of any health program, e.g. vaccination programs 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 14 Role of Statistics 1. Identify and develop treatments for disease and estimate their effects 2. Identify risk factors for diseases 3. Design, monitor, analyze, interpret, and report results of clinical studies 4. Develop statistical methodologies to address questions arising from medical/public health data 5. Locate, define and measure extent of disease 6. Ultimate objective  improve the health of individuals and community 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 15 Scientific Process in Conducting Research Design and Identify a Formulate a Collect data conduct study, problem hypothesis Sampling Draw Record and Analyze Data Conclusions Organize Data 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 21 Types of Statistics Statistics Descriptive Inferential - Organising, summarising - Generalising: Making & describing data statements about a population by examining - E.g. population, c. 2000 Del Siegle frequency of variables sample results - E.g. grade, percentile 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza’s previous lecture 22 Descriptive Vs. Inferential When we simply describe or summarize data, we're using descriptive statistics When we draw conclusions or extend our results to the population, we're using inferential statistics Types of Variables Data Data are the basic building blocks of statistics It refers to the individual values measured or observed Data can be derived from: Total Sample Population Medical statistics Types of Data Constant Data Variables 20 August 2024 Medical statistics Definition of Constant Data These are observations which do not vary from one person to another Examples: number of eyes, fingers and ears 20 August 2024 Medical statistics Definition of Variables These are observations which vary from one person to another or from group to others. Examples: height, family size, sex….etc 20 August 2024 Medical statistics Types of Variables Qualitative or Categorical (data that are counted) - Nominal - Ordinal Quantitative or Numerical (data that are measured) - Interval - Ratio Why is the type of variable important? The methods used to display, summarize, and analyze data depend on whether the variables are categorical or quantitative 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 30 Types of Variables Quantitative Qualitative (Numerical) (Categorical) Variables Variables Continuous Discrete Ordinal Nominal 20 August 2024 Medical statistics Qualitative variables Ordinal Nominal - Nominated variable and can - Can be put in order not be put in order 20 August 2024 Medical statistics Qualitative Variables- Examples Ordinal Nominal -Could be subdivided into - Degree of success { excellent dichotomous e.g. sex – very good – good – fair} - Multichotomous e.g. marital status and blood groups 20 August 2024 Medical statistics Categorical/Qualitative: Nominal (I) Variables that are “named”, i.e. classified, into one or more qualitative categories that describe the characteristic of interest No ordering of the different categories No measure of distance between values Categories can be listed in any order without affecting the relationship between them Nominal variables are the simplest type of variable Categorical/Qualitative: Nominal (II) In medicine, nominal variables are often used to describe the patient. Examples of nominal variables might include: Gender (male, female) Eye color (blue, brown, green, hazel) Surgical outcome (dead, alive) Blood type (A, B, AB, O) Note: When only two possible categories exist, the variable is sometimes called dichotomous, binary, or binomial Categorical/Qualitative: Ordinal (I) Variables that have an inherent order to the relationship among the different categories An implied ordering of the categories (levels) Quantitative distance between levels is unknown Distances between the levels may not be the same Meaning of different levels may not be the same for different individuals Note: The scale of measurement for most ordinal variables is called a Likert scale Categorical/Qualitative: Ordinal (II) In medicine, ordinal variables often describe the patient’s characteristics, attitude, behavior, or status. Examples of ordinal variables might include: – Stage of cancer (stage I, II, III, IV) – Education level (elementary, secondary, college) – Pain level (mild, moderate, severe) – Satisfaction level (very dissatisfied, dissatisfied, neutral, satisfied, very satisfied) – Agreement level (strongly disagree, disagree, neutral, agree, strongly agree) Quantitative Variables Continuous Discrete - Obtained by measurement - Obtained by enumeration - Its value could be integer or - Its value is always integer fractionated value value 20 August 2024 Medical statistics Quantitative Variables- Examples Continuous Discrete - Number of live births, - Weight, height, Hb, age, number of abortions, family income size 20 August 2024 Medical statistics Numerical/ Quantitative: Discrete Data Quantitative or Numerical variables that are measured in each individual in a data set, but can only be whole numbers Examples are counts of objects of occurrences: Number of children in household Number of relapses Number of admissions to a hospital Numerical/ Quantitative: Continuous Data (I) Examples of continuous variables: - Height, weight, heart rate, blood pressure, serum cholesterol, age, temperature A person’s height may be measured and recorded as 60 cm, but in theory, the true height could be an infinite number of values: - Height may be 60.123456789…………………cm or 59.892345678…………………cm Numerical/ Quantitative: Continuous Data (II) Interval Variables that have constant, equal distances between values, but the zero point is arbitrary Examples of interval variables: Intelligence (IQ test score of 100, 110, 120, etc.) Pain level (1-10 scale) Body length in infant Numerical/ Quantitative: Continuous Data (III) Ratio Variables that have equal intervals between values, the zero point is meaningful, and the numerical relationships between numbers is meaningful. Examples of ratio variables: Weight (50 kilos, 100 kilos, 150 kilos, etc.) Pulse rate Respiratory rate Relation Between Variables Independent Dependent Variables Variable 20 August 2024 Medical statistics Definition of Independent Variable The characteristic being observed or measured that is hypothesized to influence an event or manifestation (dependent variable) within the defined area of relationships under study So the independent variable is not influenced by the event or manifestation but may cause or contribute to variation in the event or manifestation. Example : Smoking 20 August 2024 Medical statistics Definition of Dependent Variable A variable the value of which is dependent on the effect of other variable (s) – independent variables – in the relationship under study Example: Cancer Lung 20 August 2024 Medical statistics Relation Between Variables Independent Dependent Variables Variable 20 August 2024 Medical statistics Relation Between Variables Independent Dependent Variables Variable 20 August 2024 Medical statistics

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