Introduction to Medical Statistics 2024-25 PDF

Introduction to Medical Statistics By: Prof. Ali Nawawi / Dr. Nuha Filfilan Family and Community Medicine 20 August 2024 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture...

Introduction to Medical Statistics By: Prof. Ali Nawawi / Dr. Nuha Filfilan Family and Community Medicine 20 August 2024 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 1 Course Specification 20/8/2024 Adapted from Medical Statistics Course Specification 2 Course Content 20/8/2024 Adapted from Medical Statistics Course Specification 3 Assessment 20/8/2024 Adapted from Medical Statistics Course Specification 4  Variables and Their Types By: Prof. Ali Nawawi / Dr. Nuha Filfilan Family and Community Medicine 20 August 2024 20/8/2024 Adapted from Prof. Ali Nawawi and Dr. Azza Ali’s previous lecture 5 Outline Definitions; data and statistics Why do we need statistics? Functions of Medical Statistics Role of Medical Statistics Preventive Medicine Steps in conducting a scientific research Types of Statistics Variables 20/8/2024 6 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 Importance of Medical Statistics in Preventive Medicine (I) To provide the magnitude of any health problem in the community To find out the basic factors of underlying ill health To evaluate the health program which was introduced in the community (success/ failure) To introduce and promote health legislation Medical statistics Importance of Medical Statistics in Preventive Medicine (II) To identify an association between two attributes such as cancer and smoking To identify signs and symptoms of a disease or syndrome, e.g. cough in typhoid is found by chance and fever is found in almost every case → the proportional incidence of one symptom or another indicates whether it is a characteristic feature of the disease or not Medical statistics Importance of Medical Statistics in Preventive Medicine (III) To test the usefulness of sera and vaccines in the field – percentage of attacks or deaths among the vaccinated subjects is compared with that among the unvaccinated ones to find whether the difference observed is statistically significant In epidemiological studies – the role of causative factors is statistically tested; deficiency of iodine as an important cause of Goiter in a community is confirmed only after comparing the incidence of Goiter cases before and after giving iodized salt Medical statistics Importance of Medical Statistics in Preventive Medicine (IV) To study the correlation between attributes in the same population To measure the morbidity and mortality To evaluate achievements of public health programs To fix priorities in public health programs To help promote health legislation and create administrative standards for oral health Medical statistics Importance of Medical Statistics in Nutrition Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, aging, and intrauterine growth retardation) 20 August 2024 Medical statistics 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 c. 2000 Del Siegle - E.g. population, 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  Levels of Measurement Higher level variables can always be expressed at a lower level, but the reverse is not true For example, Body Mass Index (BMI) is typically measured at an interval-level such as 23.4 - BMI can be collapsed into lower-level Ordinal categories such as: > 30: Obese 25-29.9: Overweight < 25: Underweight - Or Nominal categories such as: Overweight Not overweight  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  Thank you 20/8/2024 50