#Lakatos method

[omegaphilosophia]

Demarcating Science: Criteria for Distinguishing Science from Pseudoscience

The demarcation problem, which is the challenge of distinguishing science from pseudoscience or non-science, has been a topic of debate among philosophers of science for many years. There is no one-size-fits-all solution to this problem, but several proposed criteria and approaches have been suggested over time. Here are some potential solutions and criteria for addressing the demarcation problem:

Falsifiability (Karl Popper): According to Karl Popper, a scientific theory should be considered scientific if it is falsifiable. This means that for a theory to be scientific, there must be a way to test it empirically, and in principle, it should be possible to find evidence that could potentially refute or falsify the theory. If a theory is not falsifiable, it falls outside the realm of science.

Empirical Evidence: Another criterion for demarcating science from pseudoscience is the reliance on empirical evidence. Scientific claims should be based on empirical observations, experimentation, and data. If a purported scientific theory lacks empirical support and relies primarily on anecdotal evidence or testimonials, it may be considered pseudoscientific.

Predictive Power: Scientific theories often have predictive power. They can make testable predictions about future observations or experiments. The ability of a theory to make accurate and successful predictions can be seen as a hallmark of scientific validity.

Methodological Rigor: Science typically adheres to well-established and rigorous methods of inquiry, including the scientific method. The presence of systematic and well-documented research methods, peer review processes, and a commitment to critical evaluation can help distinguish science from non-science.

Progressive Research Program (Imre Lakatos): Imre Lakatos proposed a demarcation criterion based on research programs. He argued that scientific research programs should be judged by their ability to generate novel research questions and solutions. A scientific program that continually generates new questions and adapts to new evidence is considered progressive.

Consensus and Peer Review: Consensus among scientists and peer review processes can be used as indicators of scientific validity. Scientific claims that have withstood scrutiny, debate, and rigorous evaluation by experts in the field are more likely to be considered scientific.

Naturalism: Some philosophers argue for naturalism as a criterion, suggesting that scientific theories should be rooted in natural causes and explanations. Any theories invoking supernatural or unobservable entities may be considered pseudoscientific.

Historical Precedent: Examining historical cases of scientific advancement and the criteria used by scientists in the past to distinguish science from pseudoscience can provide insights into demarcation.

It's important to note that these criteria are not always clear-cut, and there may be gray areas where it is challenging to make definitive judgments. Additionally, some philosophers argue that the demarcation problem may not have a single, universal solution and that it may vary depending on the context and the specific scientific discipline under consideration. As a result, the demarcation problem remains a subject of ongoing debate and discussion in the philosophy of science.

[literaturereviewhelp]

Science is practically useful in inspiring technological progress to improve the material condition of the nation and the people in general (Gieryn, 1983). Science is empirical in nature. Its road to truth is experimentation with observable facts. In science, to check the theory deductions have to be compared with the facts of observation. Science is skeptical because it respects no authority other than the facts of nature. Science is the objective knowledge free from emotions, bias and prejudice. Science is theoretical and the scientists acquire knowledge through systematic experimentation with nature. Pseudoscience is any body of knowledge, methodology, belief, or practice that claims to be scientific or is made to appear scientific, but does not adhere to the basic requirements of the scientific method (Wikipedia). The word ‘pseudo’ implies that the science is fake or false just because there are problems with the testability criterion (Thompson, 1980). Pseudoscience is supposed to lack supporting evidence and plausibility (Goldstein, 2000). According to Muralidharan (n.d.) one is an experimented science and the other is an experienced science. Simanek (2005) emphasizes that the practitioners of all that is termed as ‘pseudoscience’ do not recognize the validity of this term. The boundaries of science and pseudoscience continue to be debated. With the help of a therapy in alternative medicine, namely Reiki, this paper will demonstrate that it is not possible to distinguish between science and pseudoscience. According to Lakatos (1970), the demarcation between science and pseudoscience is through inductivism. According to this theory only those propositions can be accepted into the body of science that describe hard facts or are inductive generalizations from them. An inductivist accepts a proposition only if it is proven true, otherwise he rejects it. If a proposition remains unproven, it is called pseudoscientific. He firmly states that science is based on hard factual propositions and inductive generalizations. The experiments of physics and chemistry are associated with this concept. The draw back here is that inductivism does not explain why certain facts rather than others were selected in the first place. How do the scientists get the inspiration to select a hypothesis? When a drop of water falls on our hand, the realization of hot or cold is an experience. Science merely explains the phenomenon of hot or cold but the heat and cold have existed even before the scientist made an attempt to study it. Certain disciplines which were earlier supposed to have features of pseudoscience, like lack of reproducibility, or the inability to create falsifiable experiments, are now accepted as science. Reiki is one such therapy which is now recognized as a branch of alternative medicine. It is now increasingly being accepted that experimental verifications is not a decisive scientific method. Rothbart confirms that experimental success is no definition of science because many clear cases of genuine science have been experimentally falsified (cited by Wikipedia). Goldstein further states that the scientific method cannot be easily defined and contains no rigid rules. Read the full article

[nicolae]

Lakatos on justificationism

According to the scientific "justificationist" method, knowledge consisted of proven sentences. Classical intellectuals (or "rationalists," in the narrow sense of the term) have accepted extremely varied - and powerful "proofs", through revelation, intellectual intuition, experience. These, with the help of logic, have allowed them to prove any kind of scientific statement. Classical empiricists accepted as axioms only a relatively small set of "factual propositions" that expressed "hard facts". The value of their truth has been established by experience and has been the empirical basis of science. Read the full article

[movingtothefarm]

Gablok.be - in English

Founded in 2019, Gablok offers a revolutionary insulated timber-frame construction method. Aiming to simplify construction and offer a simple, high-performance, and flat-pack timber house system, Gabriel Lakatos filed his patent in 2018.

A fan of interlocking building block toys from an early age, and involved in traditional construction for 25 years, he came up with the design for stacked insulated wooden blocks.

After many months of research and testing, the self-build house system has been validated by stability, acoustic, and energy performance consultants.

Do Gablock blocks require a joint?

No jointing system is required when self-building with Gablok insulated wood blocks.

The insulated wood blocks fit together indeed, like a building set, to form the structure of the wood-frame home.

The individual insulated wood blocks of the exterior walls are actually secured together by a system of rafters laid vertically and screwed to the frame.

When a floor is completed, these rafters – fixed vertically every 40 cm – take up, à with the help of the provided screws, not only all the blocks forming the level but also the bottom and top rail. In short, they hold the entire wall together.

[anocana]

oh yeah little retrospective on this, i had this unfinished in my drafts & i think it's worth going into some more detail than i did in my 2024 reading roundup.

imo he pretty conclusively dismantles falsificationism by pointing out that 1. basically all theories have some contradictory evidence and 2. a lot of important scientific advances would be impossible to fit into that paradigm, especially heliocentrism (which made a lot of predictions that contradicted accepted knowledge and observation, but fit into certain theoretical/philosophical/theological priorities of its early supporters). this has a lot in common w the kuhn revolutions idea but he thinks kuhn is still overtheorizing things. i think he's also correct to point out that different sciences have different and not necessarily compatible perspectives, both on the pictures of the world they prescribe and in the methods they use. i'm not convinced that these critiques are as all-encompassing as he thinks they are, to the point of total opportunism or "anarchism"; a more lakatos-style description of science in terms of productive vs unproductive research programs feels like it'd survive them.

insofar he's saying "science should be considered more as a historical phenomenon than a pure principled category" this is mostly fine, though i think he's giving up prematurely on characterizing what distinguishes that historical phenomenon from others. when he's saying "philosophers of science should be describing science as it actually exists instead of telling scientists what to do", the active project prescribed is a good one but the negative side can shade into pure status quo apologia, as seen in certain other post-positivist analytics. and the political side of his critique, as i covered in the 2024 books post, has a few decent points but mostly fails in the very self-serving ways he makes it

most of the way through Against Method and he's bringing in the Whorf and the questionable anthropology of ancient Greek thought. so far my impression is that he's got several good points but is overstating his case

[the-ephemeral-ethereal]

Science... is often a matter of challenging rather than following the lessons of observation.

from Theory and Reality by Peter Godfrey-Smith 

[geopolicraticus]

Getting to Definitions and Then Getting beyond Them

Transcending our Paradigmatic Formulations of Knowledge

I can understand the frustration that some feel about those of us who focus on definitions. I have been there myself. In some domains of inquiry I have little or no interest in definitions, but when it comes to the study of civilization, I am intensely interested in converging upon an adequate definition of civilization. I don’t look at a definition of civilization as an end in itself, but I do see the importance of clarifying our conception of civilization to the point that we can clearly and ambiguously formulate exactly what it is we are talking about when we talk about civilization; I want to make what we know about civilization explicit.

To date, I have formulated eight definitions of civilization—one of them, my pragmatic definition of civilization, I just used in Civilization and Urbanization—all of which eight definitions hang together in some kind of conceptual framework that could serve as the basis for the analysis of civilization, and each of which definitions highlight a particular aspect of that which we informally think of as exemplifying civilization.

It has been said that, while science begins with definitions, philosophy culminates in definitions. This is an oversimplification, but it points to features of scientific and philosophical thought that are, at least, not wrong. Science and philosophy can both benefit from this conceptual division of labor, following which division philosophy produces definitions that are used as the point of departure in the special sciences, and then the work of the special sciences becomes the point of departure for philosophical speculation, culminating in further definitions that are used in turn as the point of departure for further science.

A philosophy of civilization might produce a definition of civilization, which then could be employed in a science of civilization as a point of departure. An elaborated science of civilization would, in turn, produce a great deal of material for philosophical reflection, and philosophically reflecting on a science of civilization might bring us to further definitions, to be used in further science. I am not suggesting that this is the only or the optimal way that science and philosophy can work cooperatively to expand human knowledge, but it is at least one schematic way of understanding possible cooperation between disparate disciplines that usually, where they intersect, came into conflict.

So even though I am intensely interested in definitions of civilization, and I can see the possibility of a philosophy of civilization that would culminate in a definition of civilization, I would not see our scientific knowledge and understanding of civilization to be finished and completed after having arrived at a definition of civilization that seems to be prima facie adequate. One might think of a definition as a paradigmatic formulation of knowledge, but no paradigm lasts forever. The process of both expanding and refining knowledge goes on, whether under the umbrella of science or philosophy is indifferent to me, and the definitions at which we arrive, or from which we depart, are only conventional markers in the progress of our knowledge. Definitions, then, might be regarded as boundary stones in the demarcation of science and philosophy, but they are demarcations within the single and continuous territory of human knowledge, and this epistemic territory expands as we set up a new boundary marker only to immediately trespass the limit that it represents.

To speak of definitions as limits reminds me of one of my favorite quotes from Einstein:

“There could be no fairer destiny for any physical theory than that it should point the way to a more comprehensive theory in which it lives on as a limiting case.” (“Es ist das schönste Los einer physikalischen Theorie, wenn sie selbst zur Aufstellung einer umfassenden Theorie den Weg weist, in welcher sie als Grenzfall weiterlebt.”) from Relativity: The Special and the General Theory, chapter 22

Formulating this idea in terms of physical theory implies that it applies only to the natural sciences, but I would paraphrase Einstein in order to apply the same principle to the formal sciences: there could be no fairer destiny for any formal theory than that it should point the way to a more comprehensive formal theory in which it lives on as a limiting case. One constituent of formal theories is definition, and there could be no fairer destiny for a rigorous definition that that it should point the way to a more comprehensive definition in which it lives on as a limiting case.

It is the nature of the intellectual enterprise that we should relentlessly and remorselessly test the limits of the conceptual framework that we have formulated for ourselves. If we arrive at a definition of civilization, the first thing that we would want to do is to throw every possible empirical example in front of the definition and see if it holds up when so confronted. And if we find a chink in the armor of our rigorous definition, then we know that we have more work to do. We improve the definition, and then we test in again, and the process continues.

A definition that has gone too long unchallenged is a field of knowledge that has lain fallow too long, and we do our conceptual framework a favor by calling it into question, and so attempting to expand the boundaries of knowledge. The process of expanding that boundary consists of setting up boundary stones and then stepping beyond them: the boundary stones are the definitions, and stepping beyond the definitions means either finding novel empirical data or formulating thought experiments that point to alternatives to a concept embodied in a definition.

In the formal sciences, we cannot confront a definition with a multitude of empirical cases, but we can still confront a definition with counter-examples. We find this method employed in Lakatos��� Proofs and Refutations: The Logic of Mathematical Discovery, in which the confrontation of a proof with a counter-example is explicitly presented as a way to advance our thought. This is fundamentally a dialectical conception of knowledge. In so far as science and philosophy interact as outlined above, the interaction is a dialectic of science and philosophy, whereas internally neither science nor philosophy would necessarily need to pursue a dialectical method (although this is not ruled out). 

As intensely interested as I am in converging upon an adequate definition of civilization, I am equally interested in challenging any definition with counter-examples from terrestrial history, or with thought experiments as to how civilization might have developed elsewhere in the universe. There is no better way to advance our knowledge than to have an at least partially formalized exposition of an idea (i.e., an exposition of the idea that makes its properties explicit) challenged by a case that cannot be readily categorized by the conceptual framework within which the partially formalized idea appears. This is because the non-conforming instance makes it possible for us to reflect critically on an already partially formalized concept, which allows us to explicitly identify the property ascribed to the concept that presents a problem for the non-conforming instance. We can then reflect on the problematic property, analyzing it in light of the non-conforming instance, to determine whether we ought to alter or eliminate this property in the explicitly defined concept.

What I have written above is very abstract. Let me try to give a concrete example of the kind of process I am discussing. Let us take the example of textiles. In order to identify the earliest appearance of textiles in human history, we have to be able to identify what is a textile and what is not a textile. To do this, an explicit definition of textiles is helpful. Intuitively, we know that a textile is cloth or fabric. But what is cloth? It is easy to fall back on particular examples, and to say that, for example, linen and silk are textiles, but is felt a textile? Felt, instead of being woven like linen, is compressed. So if felt is a textile, then being woven is not an essential property of textiles.  

Some of the earliest textiles preserved are those found with Peruvian mummies, preserved by the extremely dry desert conditions (as with the example pictured above, from Paracas). Textiles have a deep history in Peru. At Guitarrero Cave (found in the Callejón de Huaylas valley in Yungay Province), artifacts have been preserved made of woven plant fibers that date from between 10,000 to 12,000 years before present (see the picture below). These weavings look more like nets used to carry bundles than they look like fabric, so are these textiles or something else? Should we think of them as netting or webbing rather than as early textiles? Do we need to revise our conception of what a textile is (and where textiles came from) in light of these very early examples of weavings? Did textiles evolve from basket weaving of plant fibers, or from sewing together progressively smaller bits of leather when our ancestors were wearing skins, or by weavings like those found in Guitarrero Cave, incrementally refined over time with smaller fibers and tighter weaving?

The instance of textiles is interesting and instructive, but it will be clear to the reader that my interest is in civilization, definitions of civilization, and challenging definitions of civilization. The earliest settled human societies of which we have an archaeological record—e.g., Göbekli Tepe—are clearly something distinct from nomadic hunter-gatherers, but are they civilizations? And thought experiments in exocivilizations can provide us with endless permutations on the idea of civilization. We can use these thought experiments to deepen and to refine our conception of civilization, and then turn this deepened and refined conception of civilization back on ourselves and our civilization today in order to better understand what it is we are doing by living in a civilized condition.

[dlittle30]

Ludwik Fleck and "thought styles" in science

Ludwik Fleck and “thought styles” in science

Let’s think about the intellectual influences that have shaped philosophers of science over the past one hundred years or so: Vienna Circle empiricism, logical positivism, the deductive-nomological method, the Kuhn-Lakatos revolution, incorporation of the sociology of science into philosophy of science, a surge of interest in scientific realism, and an increasing focus on specific areas of…

[takmiblog]

For and against method

For and Against Method: Including Lakatos’s Lectures on Scientific Method and the Lakatos-Feyerabend Correspondence

[designingprogress]

Paul Feyerabend’s Philosophy

Feyerabend was heavily influenced by the counter-culture movements of the 1960s. The central themes of his philosophy of science can be found in his seminal work Against Method. (The book was originally intended to be published as a dialogue with his friend and colleague Lakatos but the latter died before the project was finished). I will try to summarize Feyerabend’s view of science in a few points;

1.

On the issue of falsifiability, Feyerabend argues (in common with Kuhn and Lakatos) that no theory is ever consistent with all the relevant facts. Like Lakatos, he sees the use of ad-hoc postulates to save the dominant paradigm as an essential to the progress of science (see last post). However, Feyerabend goes much further than Lakatos; taking examples from the history of science, he claims that scientists frequently depart completely from the scientific method when they use ad-hoc ideas to explain observations that are only later justified by theory. To Feyerabend, ad-hoc hypotheses play a central role; they temporarily make a new theory compatible with facts until the theory to be defended can be supported by other theories.

2.

On the issue of paradigm shifts (or moving from a regressive research programme to a progressive one, as Lakatos would say), Feyerabend emphasises Kuhn’s idea that the reigning paradigm heavily influences interpretation of observed phenomena.  However, he adds to this by suggesting that in the paradigm model, the reigning paradigm would also have a stifling influence on the incoming theory; instead of being dictated by agreement with observation alone, the new theory must also agree with the old in almost every instance.

3.

Epistemological anarchism; putting the two points above together, Feyerabend concludes that it is impossible to view the progress of science in terms of one set of methodological rules that is always used by scientists; such a ”scientific method’ would in fact limit the activities of scientists and restrict scientific progress. Instead of operating according to universal and fixed rules, Feyerabend suggests that science often progresses by ad-hoc postulates that break the rules; this ‘anything goes’ view is formally known as epistemological anarchism.

4.

Science and Society: the doctrine of epistemological anarchism is considered Feyerabend’s major contribution, However, he also had a major point to make about science and society. Starting from the view that a universal scientific method does not exist, Feyerabend goes on to argue that science therefore does not deserve its privileged status in western society. Since scientific points of view do not arise from using a universal method which guarantees high-quality conclusions, there is no justification for valuing scientific claims over claims by other ideologies like religion. Indeed, he was quite indignant about the condescending attitudes of many scientists towards alternative traditions such as astrology and complementary medicine.  In Feyerabend’s view, science can be a repressing ideology in society instead of a liberating movement; he thought that a pluralistic society should be protected from being influenced too much by science, just as it is protected from other ideologies.

This pluralistic view, that science does not have a monopoly on truth and its authoritarian status in society should be questioned, went on to become a major tenet of the modern discipline of Science and Technology Studies.

Criticisms

1.

Feyerabend’s view of science is considered radical but interesting by many philosophers of science. However, one obvious criticism is that the comparison of science with cultural traditions such as religion doesn’t seem to stand up; faced with experimental evidence to the contrary, scientists do, eventually, change their story – unlike religion. No scientific theory that is in conflict with observation survives over time.

2.

A criticism from historians of science is that Feyerabend often backs his thesis by choosing the science of Galileo; time and again, Galileo is portrayed as an example of a scientist in rebellion against the science of the day. The problem with this example is that it can be argued that what we now consider the scientific method was developed after Galileo, not before; the invention of instruments such as the telescope and the microscope led to the evolution of the sophisticated method of hypothesis and experiment we call the scientific method today. Hence the Galileo-as-rebel-against-the science-of-the-day narrative is questionable.

3.

A general criticism from scientists is that an extraordinary thesis requires extraordinary evidence. Instead, Feyerabend’s thesis is based on case studies from the history of science that are debatable (see above, and last post), despite his meticulous research. Indeed, Feyerabend is sometimes accused of either misunderstanding or misrepresenting science in his examples. [For example, Feyerabend claims that the Newtonian view of gravitational acceleration was rebellious because it was in conflict with that of Galileo; most physicists consider this argument to be dead wrong. Newtonian mechanics deals with gravitational acceleration in a far more general way than Galileo, but it reduces to the Galilean case for an object is close to the earth’s surface; hence Newton is not in conflict with Galileo].  This example is fairly typical and raises concerns. Philosophers infer general conclusions from isolated case studies in the history of science; this is not ideal and it’s even more problematic if the case studies used are questionable.

4.

On the other hand, Feyerabend’s idea of scientific imperialism is considered very important indeed and led to many studies that suggest that the use of science in society has not always beneficial, including studies that show that claims of scientific legitimacy were sometimes used by the state to introduce unpopular and unnecessary measures on populations... more on this later.

[juniperpublishers-biostatistics]

Power Analysis and Sample Size Determination in Log-Rank (Lakatos) Test

Abstract

In this study, it was aimed to investigate the method of calculating the sample size for the Log-rank test developed and proposed by Lakatos (1988) in different scenarios. To that end, Type I error was accepted as 0.05 and the constant hazard rate (p) was accepted as 0.50. The test’s power in different sample sizes was calculated using the Kaplan-Meier method. Through the Monte Carlo simulation method, each situation was repeated 10,000 times, and the results were examined. According to the simulation results the test’s power increased while the total time, sample size and incidence rate increased. When the total incidence rate was 65%, the test’s power reaches up to 80%. In this case, the sample size was above 100. When using the log-rank (Lakatos) test for survival analysis studies, the results of the asymptotic power analyzes were summarized by taking into consideration the situation, group number, total and related event frequency, hazard ratio and test power of different sample scenarios. Sincethe Lakatos method avoids extreme assumption, it provided better results in the simulation study than the other methods requiring assumption.

Keywords:Simulation; Power analysis; Lakatos method; Log-rank test; Sample size

Introduction

The period of time between a given starting time and failure of a living organism or an object is called "lifetime". It is not always possible to find out the lifetime of each patient in clinical trials. Some patients may survive although the trial came to an end, while some may quit the trial or may be excluded from follow-up for some reason. Observations whose survival times are not known due to the specified potential reasons are defined as censored observations [2]. Censored data are encountered in many areas, including medicine, biology, food, engineering and quality control. The most commonly used method for estimating the survival function of a dataset containing censored observations is the Kaplan-Meier method. Kaplan-Meier (KM) method is a non-parametric method that helps calculate the life and death functions without dividing the data on lifetimes into time intervals [3]. Kaplan-Meier method assumes that censored observations and lifetimes are independent of each other. In some cases, more than one survival function can be calculated for patients treated through different methods, and the researcher may wish to test the difference between the survival functions. One of the tests employed to compare survival functions in such cases is the Log-rank test. This test is the most commonly used method for comparing the survival curves in cases where the assumption of proportional hazard is violated [4,5].

In setting up hypotheses in a clinical trial, researchers first determine the population of the research, and then select a random sample, which they think represents the population well, and finally attempt to estimate the population. So, selecting a sample large enough to represent the population is critically important in terms of the reliability and estimation power of the study. It is desired that a planned clinical trial is of an appropriate degree of significance and has a sufficient estimation power. The estimation power is often expected to be higher than 80%. If the power of the test used is low, the test may fall short in detecting a difference that actually exists [6,7]. However, calculation of the actual power of the trial is difficult as it depends on many unknown factors such as censor rate, distribution of lost data, and survival distributions of treatment groups as well as other factors such as stop time, follow-up time, Type I and Type II error rate, and size of impact. This study aims to explore, in different scenarios, the results of the Lakatos method, which is one of the methods where power analysis and sample size calculations in comparing the survival functions of two independent groups.

Methodology

In the study, Type I error was accepted as 0.05 and the constant hazard rate was accepted as 0.50. The test's power in different sample sizes was calculated using the Lakatos method. The scenario is as follows. For instance, the sample size and time interval were accepted to be equal for the treatment groups. Parameters (e.g. 0, , p, ) were calculated for each time interval. Results obtained from repetition of each situation for 10,000 times in the Monte Carlo simulation method were examined. The sample sizes were calculated using PASS (Version 11) program [8].

Lakatos method

The method developed and suggested by Lakatos [9] is based on the assumption that the occurrence of an expected event has an equal weight in all times and that the hazard rates for individuals in different groups are the same in all times [10]. Recording time, follow-up time, and time-dependent hazard rates are used as parameters. This method is based on the Markov model with the variance of the log-rank statistic and an asymptotic mean. In this method, power can be calculated for four different cases, namely, hazard rates, median survival time, survival rate and mortality rate. In this study, the power is calculated for the hazard rates.

The parameter hazard rate is determined individually for the control group and the treatment group. The median survival time (MST) is determined and can be converted into hazard rates using the following relationship:

The parameter survival rate indicates the rate of survival up to T0 (constant time point) and can be converted into hazard rates using the following relationship: .

The parameter hazard rate is determined individually for the control group and the treatment group. The median survival time (MST) is determined and can be converted into hazard rates using the following relationship:

The parameter mortality rate indicates the rate of mortality up to T0 and can be convertedinto hazard rates using the following relationship:

The proportional hazard assumption may be violated in calculating the power and sample size for the Log-rank statistic. In this case, the sample size formula based on the Markov Process, suggested by Lakatos, can be used. In this process, the survival model contains the following parameters: noncompliance, loss of follow-up time, drop-in, and delay of treatment's effectiveness over the course of the trial. The expected value and variance of the Log-rank statistic is calculated using the hazard rates and the risk rates in each different interval. Lakatos stated that in order to calculate the sample size, the trial period needs to be divided into N equal intervals. The interval should be long enough to fix the number of patients under risk and risk rate in each interval. The sample size required to obtain the test's power (1-p) can be calculated by Equation (1) below, where 0k is the hazard rate of the incident in the kth interval, k is the ratio of patients under risk in the two treatment groups in the kth interval, dk is the number of deaths that occurred in the kthinterval, and d is defined as

Results and Discussion

The simulation results obtained are given in Table 1 & 2. The test’s power increased while the duration of the trial (recording time), sample size and incidence rate increased. The same results can be seen in Figure 1 & 2 as well. When the cumulative incidence is approximately 65% and the sample size is 100 in the recording time 1, the test's power reaches up to 80%. When the cumulative incidence is approximately 73% and the sample size is 100 in the recording time 2, the test’s power is approximately 84%. Therefore, the power value increases while the survival rate in the control and treatment groups increases.

Conclusion

Calculation of sample size is a very critical stage in clinical trials. However, this stage is often bypassed due to complexity of the procedures, which may affect the reliability of the results and result in wasted time and resources used in implementing the clinical trial. In survival analyses, log-rank test is often used to compare two treatment groups. In the present study, a simulation was carried out, and the test's power was assessed through the Lakatos method, one ofthe log-rank tests, in different sample sizes. In calculating the power of the test, the hazard rate was accepted to be 0.50 and the type I error was accepted to be 0.05. Power values were calculated for the different values of recording time, cumulative incidence, and survival rates of groups. According to the results, when the recording time is 1, the test's power is approximately 80%, whereas the recording time increases, the power value rises above 80%. Thus, the test’s power increases while the recording time increases. Also, as the cumulative incidence, sample size and survival rate increase, the test's power increases as well. As can be seen in Figure 2, when thetest’s power is above 80%, the sample size is above 100.

In a simulation study conducted by Alkan et al. [6], it was shown that as the recording time increased, the sample size increased as well in order to achieve a power above 80%. Sample sizes for achieving a power above 80% were found to be 270, 310 and 410. In their simulation study, Lakatos & Lan [1] calculated the test's power to be approximately 90% as the sample size and incidence rate increased. Therefore, they noted in their studies that the Lakatos method gives more accurate results compared to other methods, particularly under the assumption of nonproportional hazard. In conclusion, working on a sample size smaller than what is required in scientific studies decreases the power of the study results, whereas working on a sample size larger than what is required means a waste of time and resources. Thus, by determining an optimum sample size in accordance with the research hypothesis in the beginning of the study, it is possible to ensure the reliability of the study results and prevent the waste of resources.

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[fdmllll]

The whole history of the canonical philosophers of science since Popper (Kuhn, Lakatos, Feyeraband) can be viewed as a history of so many failed assassination attempts or compromises against competitive dynamics as the sole method of coming to know truths which are neither subjective nor arbitrary.

5/6/22

[literaturereviewhelp]

Marx involved himself with scientific as well as dialectical doctrines and hence referring his approach as scientific and dialectic approach. This means that Marx believed that dialectic reasoning could have great significance in scientific methods. By demystifying various misconceptions regarding the work of Marx and evaluating the manner of bringing scientific approaches to support his entire sociological idea, his acquisitive historical perception and in his biased economy, this writing aims at analyzing the methodological doctrines of Marx’s views. Marx’s methods Generally, Marx successfully overcomes the conventional dualism separating the empirical approach and the speculative approach. There is good evidence that he managed to support all the arguments he presented by as much evidence as possible. His major contributions came after many years of studies and establishment of factual statements. However, contrary to empiricism, Marx idea does not begin with swine facts (Abdel-Malek 1963). In addition, his idea does no remain contented with plain inductive generalisations drawn from them. Marx initial stand is a philosophical view and a good critical examination of the original pertinent knowledge. The preliminary substantiation is just an important element of the backdrop from which he comes up with the entire network of the abstract scientific impression, gifted with a remarkable power of explanation. This embellishment of a new theoretical gadget constitutes the most significant and ingenious part of the scientific work of Marx (Lakatos 1970). According to Marx’s view, science must not only base on the description and explanation of specific occurrence, but should also incorporate an analysis of the entire structures of the social conditions considered in their entirety. This provides an explanation of the reason that makes Marx’s methodology to lack a clear distinction into twigs as well as disciplines (Edgar & Sedgwick 2007). Therefore, capital does not just belong to the field of economics but also belongs to the other fields like political science, history, sociology, philosophy and law. Despite the fact that the concept of totality bears a significant role in Marx’s methodology, his idea is not truly synthetic Read the full article

[crimsonpublishers]

New Questions of Methodology of Scientific Knowledge and History of «Research Programs» (Methodological Approaches of Lakatos, Popper, Kuhn and Duhem)_Crimson Publishers

New Questions of Methodology of Scientific Knowledge and History of «Research Programs» (Methodological Approaches of Lakatos, Popper, Kuhn and Duhem) by Kochetkov AV in Crimson Publishers: Peer Reviewed Material Science Journals 

The article first studies the methodological approaches of Lakatos, Popper, Kuhn and Duhem. A comparative analysis of the methodological approaches of different authors is carried out. The advantages and disadvantages of different methods of scientific knowledge are compared. In the article, using the methodological approach, the analysis of the current state of the molecular theory of matter is carried out. Analysis of the modern theory of molecular physics is mainly based on the theory of research programs of I. Lakatos. 

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[nicolae]

SetThings - Lakatos on justificationism

https://www.setthings.com/en/e-books/lakatos-on-justificationism/

Lakatos on justificationism

According to the scientific “justificationist” method, knowledge consisted of proven sentences. Classical intellectuals (or “rationalists,” in the narrow sense of the term) have accepted extremely varied – and powerful “proofs“, through revelation, intellectual intuition, experience. These, with the help of … Read More

[soniatao]

EVALUATING BY NARRATION (W7)

Telling a story helps people to understand different scenarios or happenings. You’re able to showcase the usage of something through representation, which helps the audience to get a better understanding of something. Showing a real context helps to generate a human experience, like empathy, of the audience. In relation to design, storytelling has lots of benefits. Generally you could say, that it’s a very important tool to help us evaluate success or failure, or to rethink our concept. Basically it’s a mirror of purposes and intentions of your own design concept, similar like the purpose of a prototype. Storytelling can help us for gain funding as well, a way to sell your own idea.

There’s not only a positive side about it, storytelling can be counterproductive though. The danger of staying at the level of illustration can occur really fast. Another aspect is, that it can be manipulative, for example TED Talks. The danger here is a certain automatic guidance of the one who narrates the story. It can happen that stories are too simplistic and not open enough. Therefor, you need a lot of responsibility when publishing a storyboard. A successful story can turn into a failure as well, accordingly to Joëlle.

Designers are in the constant mode of selling their design to customers, clients, potential kickstarter funders, etc. To do so, it’s always important to keep the aspects like business priorities, what it can contribute to the world, politics, culture and emotions, and ones’ marketing-presentation strategy in mind. Thus it’s always important to stay true to yourself and the other side. Showing empathy and sympathy to the outside world helps you to get further. Honesty and authenticity are other important parameters to enhance your chance in the big world.

READINGS

Auger, James. 2012. “Demo or die: Overcoming oddness through aesthetic   experience”. In Why Robot? Speculative Design, the domestication of technology and  the considered future. PhD Thesis. RCA, London. 

 Hertz, G. & Parikka, J. 2012. “Zombie Media: Circuit Bending Media   Archaeology into an Art Method”. In Leonardo. 45:5. 424–430. Ishii, Hiroshi & Ullmer B. 1997. “Tangible Bits: Towards Seamless Interfaces   between People, Bits and Atoms”. In Proceedings of CHI ‘97. 

Ishii, Hiroshi, Lakatos, D., Bonanni, L. & Labrune, J. “Radical Atoms: Beyond   Tangible Bits,Toward Transformable Materials”. In Interactions. 19:1. January/  February 2012. 38-51.  Kim, J., Lund, A. & Dombrowski. 2010. “Mobilizing Attention: Storytelling for   Innovation”. In Interactions.

Loch, Christopher. 2003. Moving Your Idea Through Your Organisation. In   Laurel, Brenda (ed.). Design Research. Methods and Perspectives.