Limitations and Delimitations in Research: Types, Examples and Real Data

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Quick answerLimitations are weaknesses of a study that the researcher could not fully control, such as a small or unrepresentative sample, measurement problems or a short time frame. Delimitations are boundaries the researcher chose on purpose, such as the population, location, period or variables included. Limitations explain how far the results can be trusted; delimitations explain what the study deliberately covers.

Reviewers almost always look for an honest discussion of limitations: a study that admits its limits is easier to trust than one that claims none. Below we compare limitations and delimitations, list the most common types, and then show them on a real example: ScholarsColab’s own research data.

Limitations vs delimitations at a glance

Limitations Delimitations
What they are Weaknesses outside the researcher’s full control Boundaries the researcher sets deliberately
Question they answer “How far can these results be trusted and generalised?” “What exactly does this study cover, and what not?”
Typical examples Small sample, self-reported data, missing records, short follow-up Only undergraduate students, only 2015–2024, only one region, only two variables
Where they appear Usually the Discussion, before the conclusion Usually the Introduction or Methods (scope of the study)
Effect on results May bias or weaken them Narrow where they apply
(a) The populationchosen boundarymissingdata(b) What each term coversDelimitationa boundary you chosee.g. one region, 2015 to 2024Limitation: missing datasome records unavailableLimitation: measurementthe gauge reads off targetn=24Limitation: small sampletoo few for small effects
Figure 1. (a) A population with the boundary chosen by the researcher (delimitation) and an area with missing data. (b) The delimitation and three common limitations.

The most common types of limitations

Type What it means Example
Sample size Too few participants or cases to detect real effects A pilot study with 24 patients
Sampling (selection) The sample does not represent the population An online survey reaching only internet users
Measurement Instruments or self-reports are imprecise Self-reported hours of sleep
Design The design cannot show cause and effect A cross-sectional study showing only association
Data availability Missing, incomplete or old data Hospital records without lifestyle information
Time Follow-up too short to see long-term effects A 3-month study of a chronic condition
Generalisability Results may not hold in other settings A simulation tested on one network topology

Example: the limitations and delimitations of ScholarsColab’s own data

To show what an honest limitations statement looks like, we apply it to the dataset behind our research methodology guides. Our data: 42,750 papers, mostly published between 1998 and 2026, by 1,014 ScholarsColab mentors (data updated 1 November 2026).

Step 1
State the delimitations: what the data deliberately covers. The dataset includes only publications listed on the Google Scholar profiles of PhD researchers who mentor on ScholarsColab. Methods are identified from paper titles only. Those are choices, not flaws: they define the scope.

Step 2
State the limitations: what could distort the results. The mentors are not a random sample of all researchers. Some fields are represented much more than others:

Papers by disciplineEngineering & computer science49.6%21,188 papersMedicine & health16%6,824 papersLife & environmental sciences12.5%5,327 papersOther or unclassified7.7%3,298 papersPhysical sciences & mathematics7%2,999 papersManagement, economics & finance5.5%2,362 papersSocial sciences & education1.8%752 papers
Share of all papers in the dataset by the mentor's discipline. Source: ScholarsColab Research Methods Index.

Engineering & computer science alone accounts for 49.6% of the papers, so this group of researchers does not mirror research as a whole. This is a sampling limitation: any figure on this site describes this group of researchers and may not hold for research as a whole.

Step 3
A measurement limitation. Because methods are detected from titles, papers that use a method without naming it in the title are missed. Only 7,951 of the 42,750 papers (18.6%) name a recognisable method or design in their title; the rest cannot be classified from the title alone.

Step 4
Explain what the limitations mean for the results. A good limitations section does not only list weaknesses; it says how they affect the conclusions. Here: comparisons between fields are reliable for the fields with many papers, uncertain for fields with few, and the share of each method is a lower estimate.

What reviewers notice. Limitations stated vaguely (“this study has some limitations”) or left out entirely are a frequent reviewer comment. Naming the specific weakness, its likely direction (over- or underestimation) and how future work could address it reads as rigour, not weakness.

A simple structure for reporting limitations

  1. Name the limitation specifically (for example, “the sample came from two urban hospitals”).
  2. Explain its possible effect on the results (“results may not apply to rural populations”).
  3. Say what was done to reduce it, if anything (“we adjusted for age and income”).
  4. Suggest how future research could address it (“a multi-centre study including rural sites”).

Frequently asked questions

What is the difference between limitations and delimitations?

Limitations are weaknesses the researcher could not fully control and that may affect the results. Delimitations are boundaries the researcher chose deliberately, such as the population, period or variables, which define the scope of the study.

Where do limitations go in a research paper?

Most journals expect limitations in the Discussion section, usually just before the conclusion. Some journals ask for a separate “Limitations” subsection; check the author guidelines of your target journal.

Do limitations make a paper weaker?

No. Every study has limitations. Reviewers trust a paper more when its limitations are stated clearly, together with their effect on the results, than when they are hidden.

Are limitations the same as scope?

Scope is described by the delimitations: what the study covers. Limitations are about how reliable and generalisable the findings are within that scope.

Use this data in your own work

Use this data in your own research. Download the aggregated figures behind these charts (counts, medians and shares by type of paper, period, method and discipline) as a CSV file. Please cite it as:ScholarsColab (2026). ScholarsColab Research Methods Index [Data set]. Vidhilekha Soft Solutions Pvt Ltd. Retrieved 1 November 2026, from https://scholarscolab.in/research-methodology/. Licensed under CC BY 4.0.Download the data (CSV) →

More research methodology guides

About the data on this page. The ScholarsColab Research Methods Index is built from the Google Scholar publication lists of PhD researchers who mentor on ScholarsColab, and is updated daily as mentors and publications are added. Methods, designs and paper types are identified from titles, so papers whose titles do not mention them are not counted in those groups. The mentors are not a random sample of all researchers (engineering and computer science are strongly represented), so the figures describe this group of researchers and may not apply to research as a whole.