Name: how random assignment reduces bias
Uploaded: 2023-04-30T12:28:07.000Z
Duration: 1 min 13 s
Channel: JoVE

K12 Standards

Virginia  Standards of Learning

HIgh School

Chemistry

CH.1

CH.1.c

Randomized Experiments

Die Randomisierung ist eine statistische Methode, bei der die Teilnehmer nach dem Zufallsprinzip einem Experiment oder einer Kontrollgruppe zugeordnet werden, wobei davon ausgegangen wird, dass jeder Teilnehmer eine faire Chance hat, ausgewählt zu werden.
Die Randomisierung hilft, Verzerrungen zu vermeiden, die bei der Auswahl der Probanden auftreten können, oder versehentliche Fehler während und nach dem Experiment.
Die einfache Randomisierungsmethode unterteilt die Proben in zwei Gruppen, indem eine Münze geworfen oder ein Würfel geworfen wird.
Merkmale der Stichprobe, wie z. B. das Geschlecht, können sich jedoch auf die Ergebnisse auswirken und als Blockierungsvariable wirken. In solchen Fällen wird die Blockrandomisierung verwendet, die die Stichproben nach Geschlecht in Blöcke unterteilt. Je nach Behandlungsgruppe werden die Individuen in jedem Block nach dem Zufallsprinzip in kleinere Gruppen eingeteilt.
Bei der stratifizierten Randomisierung werden prognostische Variablen wie Geschlecht und Body-Mass-Index gruppiert und bilanziert. Mit diesen beiden Kovariaten sind sechs Kombinationen bzw. Schichten möglich. Die Individuen innerhalb dieser Schichten werden dann nach dem Zufallsprinzip einer Behandlungs- oder Kontrollgruppe zugeordnet.

randomisierte experimente

Der Randomisierungsprozess beinhaltet die zufällige Zuweisung von Studienteilnehmern zu experimentellen oder Kontrollgruppen basierend auf der Wahrscheinlichkeit einer gleichmäßigen Zuweisung. Die Randomisierung soll die Auswahlverzerrung eliminieren und bekannte sowie unbekannte Störfaktoren ausgleichen, sodass die Kontrollgruppe der Behandlungsgruppe so ähnlich wie möglich ist. Ein Computerprogramm und ein Zufallszahlengenerator können verwendet werden, um Teilnehmer auf eine Weise den Gruppen zuzuweisen, die die Verzerrung minimiert. Einfache Randomisierung Einfache Randomisierung bezieht sich auf zufällige Zuweisungen basierend auf einer einzelnen Sequenz. Die Auswahl einer Person für eine Gruppe bleibt völlig zufällig. Das Werfen einer Münze ist die häufigste und grundlegendste Methode der einfachen Randomisierung. Blockrandomisierung Sie besteht darin, Teilnehmer zufällig verschiedenen Gruppen zuzuweisen, um eine gleiche Stichprobengröße der Teilnehmer zu produzieren. Diese Methode stellt sicher, dass die Stichprobengrößen im Laufe der Zeit über die Gruppen hinweg ausgeglichen sind. Jeder Block ist klein und ausgeglichen, mit vorher festgelegten Gruppenzuweisungen, sodass die Anzahl der Teilnehmer in jeder Gruppe immer ähnlich ist. Stratifizierte Randomisierung Bei der stratifizierten Randomisierung werden Kovariaten kontrolliert und ausgeglichen. Diese Methode ermöglicht es, die Basischarakteristika der Teilnehmer (Kovariaten) zwischen den Gruppen auszugleichen. Um die Auswirkungen einer Kovariate auf eine abhängige Variable abzuschätzen, muss der Forscher spezifische Kovariaten identifizieren. Teilnehmer werden basierend auf der stratifizierten Randomisierung dem entsprechenden Block von Kovariaten zugewiesen, wodurch separate Blöcke für jede Kombination von Kovariaten erstellt werden. Nachdem alle Teilnehmer identifiziert und in Blöcke eingeteilt wurden, wird die einfache Randomisierung verwendet, um sie einer der Gruppen innerhalb jedes Blocks zuzuweisen.

Randomisierte Experimente

Beim Randomisierungsprozess werden die Studienteilnehmer nach dem Zufallsprinzip in Versuchs- oder Kontrollgruppen eingeteilt, basierend auf ihrer Wahrscheinlichkeit, gleich ...

Education

Lehre

JoVE Core

Statistics

Statistik

Unit 1

Einheit 1

Statistics in Practice

Statistik in der Praxis

KEY TERMS AND CONCEPTS

KERNBEGRIFFE UND KONZEPTE

how random assignment reduces bias

Random assignment helps researchers place participants into experimental and control groups. It gives each person an equal chance of being assigned to either group. This process is used to reduce selection bias and to balance known and unknown confounding factors, so the control group is as similar to the treatment group as possible.

A computer program or a random number generator can make the assignment process less biased. Simple randomization is the most direct method. It uses a single random sequence, and each person stays completely random in the group assignment. Flipping a coin is the most common example of simple randomization.

Block randomization is used when researchers want equal sample sizes across groups over time. It randomly assigns participants in small, balanced blocks. Each block has predetermined group assignments, so the number of participants in each group stays similar as the study continues.

Stratified randomization keeps baseline characteristics, or covariates, balanced between groups. Researchers first identify the specific covariates they want to control. They then place participants into separate blocks for each combination of covariates. After that, simple randomization is used within each block to assign participants to one of the groups.

How Random Assignment Reduces Bias

what is an experiment?

Random Assignment in Experiments

Random assignment in experiments helps researchers test cause and effect between two variables. An experiment is a planned activity carried out under controlled conditions. It is used to study how one variable affects another. The variable that causes change is the explanatory or independent variable. The variable that changes in response is the response or dependent variable. In a randomized experiment, the researcher changes the explanatory variable and measures the response variable. The...

study design in statistics

Experimental and Observational Study Types

Study design in statistics helps researchers collect and analyze data from variables in a specific research problem. It supports stronger experiments and more reliable data. Questions about aspirin and heart attacks, fertilizer and rose growth, or fatigue and alcohol-related driving risk all depend on careful study design. Study designs are usually grouped into two main types: descriptive and analytical studies. Descriptive studies describe the variables and answer what is happening, rather...

observational studies

Types of Observational Research Methods

Observational research methods let scientists study events without changing them. The researcher does not intervene, so the response variable and the outcome are left alone. These studies are used to look for patterns and relationships in real-world settings. There are three main types of observational studies: prospective, retrospective, and cross-sectional. Each type collects information in a different way. Together, they help researchers answer questions about health, behavior, and risk. <br...

experimental designs

Types of Experimental Design

Experimental design is a systematic way to study how an independent variable affects a dependent variable. Researchers use it to compare results and judge whether a treatment or intervention changes the outcome. Three common experimental designs are pre-experimental design, true experimental design, and quasi-experimental design. Each one supports research in a different way, depending on how groups are formed and how the data are collected. In pre-experimental design, the researcher compares...

randomized experiments

Random assignment helps researchers place participants into experimental and control groups. It gives each person an equal chance of being assigned to either group. This process is used to reduce selection bias and to balance known and unknown confounding factors, so the control group is as similar to the treatment group as possible. A computer program or a random number generator can make the assignment process less biased. Simple randomization is the most direct method. It uses a single...

crossover experiments

Repeated-Measures Study Design

Crossover experiments are a repeated-measurements study design used in science and medicine. In this design, the same experimental units receive all treatments during different time periods. That setup helps compare how each treatment performs within the same group. These studies are used in psychology, the pharmaceutical industry, agriculture, and medicine. They can work with smaller sample sizes because the samples act as their own controls. That makes crossover designs useful when...

controls in experiments

Why Control Groups Improve Experiment Results

Control groups help experiments produce more reliable results. They reduce bias and make it easier to measure the dependent variable. In an experiment, controls have the same features as the treatment groups but are not affected by the independent variable. Researchers sort data into control and experimental conditions to see the relationship between the independent and dependent variables. A randomized experiment includes a control group that receives an inactive treatment. The control group...

bias

Biased Sampling and Fair Tests

Bias is any tendency that keeps a question from being unprejudiced. In research, bias appears when one outcome or answer is favored over others during sampling or testing. It can happen at many stages, including study design, data collection, analysis, and publication. A common form is sampling bias. This happens when a sample is taken from a population and some members are less likely to be chosen than others. In a fair sample, each member of the population should have an equally likely...

blinding

Placebos and Bias in Randomized Trials

Placebos and blinding are key tools in randomized control trials, or RCTs. They help researchers reduce bias, which can affect study results. In a blinded study, participants do not know which treatment they are receiving. A placebo is a dummy treatment that does not contain the active treatment. Researchers use a placebo in the control group to compare against the treatment group. This helps balance the effects of being in an experiment with the effects of the active treatment itself. A...

clinical trials

How Clinical Trials Test New Treatments

Clinical trials test new treatments in people to check safety and effectiveness. These experimental studies can look at drugs, diet methods, and medical devices. Researchers use statistics to turn collected data into reasonable and accurate conclusions, so they can make sound decisions when results are uncertain. Statistics also help medical researchers reduce error and bias. That matters because clinical trial data can be influenced by chance or by uneven study design. Careful analysis...

key terms and concepts

Learn how random assignment helps reduce selection bias, balance confounding factors, and use simple, block, and stratified randomization in experiments.

How Random Assignment Reduces Bias | JoVE K12

statistics

JoVE Core Statistics introduces the concepts and application of the collection, analysis, presentation, and interpretation of data to students. These animated lessons provide an understanding of statistics beneficial to students from a wide range of disciplines. Additionally, the scientist-in-action videos demonstrate the application of related concepts in classical and original research experiments performed in today's laboratories worldwide

Physical Science

PS.1

PS.1.b

Physics

PH.1

PH.1.b

Texas Essential Knowledge and Skills

High School

CHEM.1

CHEM.1.B

The Scientific Method

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• ask questions that arise from careful observation of phenomena, examination of a model or theory, unexpected results, and/or to seek additional information
• determine which questions can be investigated within the scope of the school laboratory 
• make hypotheses that specify what happens to a dependent variable when an independent variable is manipulated
• generate hypotheses based on research and scientific principles 
• define design problems that involve the development of a process or system with interacting components, criteria and constraints

CH.1.a

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Ethics in Research

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The student will demonstrate an understanding of scientific and engineering practices by Planning and carrying out investigations
• individually and collaboratively plan and conduct observational and experimental investigations 
• plan and conduct investigations or test design solutions in a safe manner, including planning for response to emergency situations 
• select and use appropriate tools and technology to collect, record, analyze, and evaluate data

CH.1.b

Research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or ...

What is an Experiment?

An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two ...

Study Design in Statistics

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Observational Studies

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally ...

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in ...

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more ...

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected ...

Blinding

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Clinical Trials

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How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. ...

How Data are Classified: Numerical Data

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Ogive Graph

An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, ...

Histogram

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Relative Frequency Histogram

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What is a Mode?

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Midrange

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Multiple Bar Graph

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Range

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Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the ...

Standard Deviation

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Pie Chart

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Standard Error of the Mean

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Calculating Standard Deviation

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Arithmetic Mean

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Mean From a Frequency Distribution

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The student will demonstrate an understanding of scientific and engineering practices by Interpreting, analyzing and evaluating data
• record and present data in an organized format that communicates relationships and quantities in appropriate mathematical or algebraic forms 
• use data in building and revising models, supporting explanations for phenomena, or testing solutions to problems 
• solve problems using mathematical manipulations including the International System of Units (SI), scientific notation, derived units, significant digits, and dimensional analysis 
• analyze data using tools, technologies, and/or models (e.g., computational, mathematical) to make valid and reliable scientific claims or determine an optimal design solution 
• analyze data graphically and use graphs to make predictions 
• differentiate between accuracy and precision of measurements
• consider limitations of data analysis when analyzing and interpreting data 
• analyze data to optimize a design

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In hypothesis testing, a sample ...

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Types of Hypothesis Testing

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When the null and alternative hypotheses are stated, it is observed ...

The student will demonstrate an understanding of scientific and engineering practices by constructing and critiquing conclusions and explanations
• construct and revise explanations based on valid and reliable evidence obtained from a variety of sources 
• apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena or design solutions 
• compare and evaluate competing arguments in light of currently accepted explanations and new scientific evidence 
• construct arguments or counterarguments based on data and evidence 
• differentiate between scientific hypothesis, theory, and law

CH.1.d

Dimensional Analysis

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Modeling and Similitude

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This setup predicts the ...

Typical Model Studies

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The student will demonstrate an understanding of scientific and engineering practices by developing and using models
• evaluate the merits and limitations of models 
• develop, revise, and/or use models based on evidence to illustrate or predict relationships 
• use models and simulations to visualize and explain the movement of particles, to represent chemical reactions, to formulate mathematical equations, and to interpret data sets

CH.1.e

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It involves the sender encoding an ...

Communication Objectives

Marketing communication objectives refer to the strategic goals that guide promotional activities.
They set the stage for messaging strategies, content ...

The student will demonstrate an understanding of scientific and engineering practices by obtaining, evaluating, and communicating information
• compare, integrate, and evaluate sources of information presented in different media or formats to address a scientific question or solve a problem 
• gather, read, and evaluate scientific and/or technical information from multiple authoritative sources, assessing the evidence and credibility of each source 
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CH.1.f

How Random Assignment Reduces Bias

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